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More and more organizations are now opening up to endless possibilities that data holds, necessitating the presence of people who are capable of unlocking meaningful and actionable insights from the vast amount of data. These people are called data scientists, and what they do—study data and extract insights, is called data science. Data science has become a prominent field over the last few years, and in India too. Consequently, many people are riding the wave and shifting to data-driven careers. A Ph.D. in data science is considered to be a prestigious qualification to advance in a data career. Here is a list of some top Indian institutes for Ph.D. in data science.

The initial thought that almost every person seeking a Ph.D in data science comes across is to explore the IITs. The Indian Institute(s) of Technology are one of the country’s most prestigious centers of (engineering) excellence. 

Some Ph.D. in Data Science Programs at IITs

We have covered a few IITs offering comprehensive science and data science doctorates. Have a look.

The Indian Institute of Technology Madras (IITM) is one of the oldest institutes catering to higher education in engineering. It was established in 1959 by Prof. Humayun Kabir, Union Minister of Scientific Research and Cultural Affairs, after the first Indo-German agreement in Bonn. With over 16 academic departments and some research centers, IITM ranks among the top engineering institutes for postgraduate and doctorate students.

IIT Madras offers research programs in several areas like biotechnology, ocean engineering, structural analysis, element modeling, data sciences, and many more. The institute also offers joint Ph.D. programs with universities like the University of Singapore, the University of Bordeaux, Michigan State University, and a few others. Refer to the research programs’ page for more details.

• IIT Hyderabad

The Indian Institute of Technology Hyderabad (IITH) , a relatively newer IIT institution branch, was founded in 2008. As one of the nation’s most sought-after institutions for science and technology, IITH has continuously been listed among the top 10 engineering and Ph.D. institutes in India. The institute offers a number of undergraduate, postgraduate, and doctoral programs in all classical engineering disciplines and interdisciplinary areas like artificial intelligence.

IITH offers regular Ph.D. programs in the following departments: biomedical engineering, artificial intelligence, chemical engineering, climate change, physics, engineering science, civil engineering, mechanical & aerospace engineering, and many other domains. Specifically for a Ph.D. in artificial intelligence or a Ph.D. in data science, in India, IITH is an excellent place to enroll. To know more about the courses and admission requirements, refer here .

Indian Institute of Technology Delhi (IITD) is one of the 23 Centers of Excellence for engineering, research, and development in science and technology. It was established in 1961 as College of Engineering and was later renamed as IIT-Delhi in 1963. The institute is an excellent place for students to wish to study engineering, sciences, and even business administration.

The Yardi School of Artificial Intelligence (ScAI) at IIT Delhi offers comprehensive Ph.D. programs in both core and advanced artificial intelligence and data science. The data science Ph.D. course will also include machine learning techniques, mathematical foundations, and applications of artificial intelligence in the field. For more information on Ph.D. programs offered by the Yardi School of Artificial Intelligence, refer to the website .

• IIT Jodhpur

IITJ, the Indian Institute of Technology Jodhpur , was established to promote technology-based education and research in India in 2008. The Institute is committed to a multidisciplinary approach to developing new technologies and furthering them as educational courses via its cutting-edge laboratories, academic degree-related activities, and coordinated research efforts. 

IITJ offers M.Tech, data science Ph.D. courses, and an integrated data science Ph.D. The doctoral program focuses on inculcating deep knowledge and computational thinking skills among students. Students who enroll in Ph.D. in data science will also develop a strong understanding of machine learning, data mining, modeling & simulation, numerical analysis, and other data-related technologies. For details, check out the main website . 

Read More: Made In Bengaluru: A Kannada Film To Be Released In The Metaverse

Some Other Data Science Ph.D. Courses in India

Have a look at some more data science Ph.D. courses and institutes offering them.

• BITS Pilani

Birla Institute of Technology & Science, BITS Pilani , is the epitome of higher education. The Institute was established in the early 1900s as a small school to train youth. Over the years, it expanded into a set of colleges for higher education that later formed the university. BITS is known to provide top-of-the-line technical education to students all over the world who are admitted on a merit basis. 

Ph.D. in Data Science at BITS PILANI

BITS Pilani offers several areas of doctoral education in the data science domain. These areas include:

• Artificial intelligence, Machine Learning, and Data Mining
• Computer Architecture, Embedded Systems & Robotics
• Data Warehousing, Databases, and Advanced Databases
• High-Performance Computing and Distributed Systems
• Image Processing & Multimedia
• Networking and Mobile Computing
• Algorithms & Theoretical Computer Science 

The institute primarily offers full-time doctoral courses. Other details, including the fee structure and shortlisting criteria, can be found on the website .

• Ph.D. in Data Science: Christ (deemed to be) University

The CHRIST University was founded by St. Kuriakose Elias Chavara, a social reformer, and educationist. It was established as a college with an aim to bring breakthroughs in the Indian higher education landscape using modern curricula and holistic education. After several years of operating as a college, the UGC (University Grants Commission) accredited it with the autonomy of being identified as an institution in 2006. Since then, the (deemed to be) university has focused on Bachelor’s, Master, and Doctoral degrees in social sciences, engineering, architecture, sciences, commerce, and law.

CHRIST’s doctorate of data science is a unique amalgamation of computer science, mathematics, and statistics. The Ph.D. program also covers the underlying computational models and mathematical research to give students a dynamic learning experience in the data domain. For details about the course and course fee, check the course page .

• Indian Statistical Institute

If you are wondering which university is best for data science Ph.D. in India, then the Indian Statistical Institute (ISI) is your answer. Mahalanobis established the prestigious institute in 1931 as a small statistics laboratory in the Presidency College. Soon enough, many people began taking an interest in statistical research, and the wave took over the institute. ISI offers several prestigious postgraduate and doctoral programs across multiple fields, like humanities, commerce, IT, engineering & architecture, management, and sciences. 

For a Ph.D. in data science domain, ISI offers research fellowships in Statistics, Quantitative Economics, Computer Sciences, Mathematics, and Reliability & Operations Research. Specifically, ISI is an excellent option if you are looking for a Ph.D. in statistics in India. To know more about the program details, refer to the website . 

• Ph.D. in Data Science at IISc Bangalore

The Indian Institute of Science (IISc) Bangalore is a reputed research university for higher education in the fields of engineering, management, design, and science. The Department of Computational and Data Sciences (CDS), a division of IISc that specializes in data sciences and computations, grants research-based doctoral degrees. 

CDS offers two research-based routes for students seeking admission to a Ph.D. in data science: Computational Science (CP) and Computer & Data Systems (CS). CDS-CP includes computational methods in areas like bio-molecular computation, structural biology, medical imaging, and other related fields. CDS-CS designs, implements, and evaluates computer hardware and software systems. For more information, refer to the website .

• Woxsen University 

Looking for an integrated data science Ph.D. in India, Woxsen University is a top university in India for data science Ph.D. and is one of the most reliable, privately-held universities in the southern part of the country. Founded in 2014, the university ranks well amongst emerging engineering and business colleges. The university aims at bringing new-age programs in multiple domains like management, architecture, design, liberal arts & sciences, and a few others. 

In doctoral programs, Woxsen offers both full-time, and executive Ph.D. focused on research and interdisciplinary subjects. It also offers a comprehensive, fully residential Ph.D. in data science. For more information, refer to the website .

• Ph.D. in Data Science at IIT Guwahati

Indian Institute of Technology (IIT) Guwahati is a prestigious higher education institution established in 1994. Being the only institute that comes in the top 100 world universities under 50 years of age, it offers comprehensive graduate, postgraduate and doctoral programs. The Mehta Family School of Data Science and Artificial Intelligence (MFSDS&AI) offers several Ph.D. courses at IIT Guwahati:

• Ph.D. in AI 
• Ph.D. in Machine Learning, Deep Learning, or Reinforcement Learning
• Ph.D. In Computer Vision, Natural Language Processing, and High-Performance Computing.

For more information about the courses and admission requirements, refer to the website .

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Programme Details

Doctor of Philosophy (PhD) in Data Science

• Open From : 21-Mar-2024
• Open Until : 04-Jun-2024

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Eligibility - 2024

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Syllabus(Academic Year-2023)1

The Doctor of Philosophy programme in Data Science is a distinctive offering that integrates principles from Computer Science, Statistics, and Mathematics. Given the pivotal role of data science and its computational models in decision-making processes across various domains, it has become a highly sought-after field in research, academia, and industry. The Department of Computer Science is dedicated to delivering a comprehensive curriculum that seamlessly combines theoretical research with practical applications in the realm of data science.

This programme is designed to cultivate dynamic researchers capable of designing sophisticated mathematical and statistical models for extracting knowledge from data. By fostering a blend of creativity and innovation, students are equipped with the skills to address complex data research problems, showcasing intellectual excellence in the fields of Computer Science, Mathematics, and Statistics..

Why choose this course?

Integrates Computer Science, Statistics, Mathematics principles for a comprehensive skill set.

Applies data science for real-world impact in diverse domains.

Highly sought-after in research, academia, and industry.

Department ensures a rich curriculum merging theory with practice.

Cultivates dynamic researchers in advanced modeling techniques.

Fosters creativity and innovation in addressing complex data problems., what you will learn.

• Master principles of Computer Science, Statistics, and Mathematics for a holistic understanding.
• Develop expertise in applying computational models to drive decision-making across diverse domains.
• Acquire sought-after skills in data science, relevant in research, academia, and industry.
• Navigate a comprehensive curriculum, seamlessly integrating theoretical research with practical applications.
• Cultivate proficiency in designing advanced mathematical and statistical models for effective data extraction.
• Foster creativity and innovation, enabling the adept resolution of complex data research challenges.

Career prospects

• Unlock diverse career paths in research, academia, and industry with sought-after data science skills.
• Attain leadership roles, leveraging expertise in Computer Science, Statistics, and Mathematics.
• Contribute to decision-making processes across domains with advanced computational modeling skills.
• Navigate dynamic roles in data analysis, research, and innovation, shaping the future of technology.
• Excel in academia, becoming a thought leader with intellectual prowess in data science disciplines.
• Drive innovation in Computer Science, Mathematics, and Statistics, making a lasting impact in diverse sectors.

(Deemed to be University)

Dharmaram College Post, Hosur Road, Bengaluru - 560029, Karnataka, India

Tel: +91 804012 9100 / 9600

Fax: 40129000

Email: [email protected]

Web: http://www. christuniversity.in

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CHRIST (Deemed to be University) is a nurturing ground for an individual's holistic development to make effective contribution to the society in a dynamic environment.

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The School of Data Science and AI at IIT Madras offers MS/PhD programmes in a variety of areas. We welcome applicants from diverse departments with an applied interest in AI/ML, as well as students from EE/CS/AI departments who are interested in fundamental research areas in AI/ML.

The applications for M.S. and Ph.D programmes are now open!

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Top Postgraduate Data Science Programmes In India – AIM Ranking 2021

Illustration by Top Postgraduate Data Science Courses In India AIM Ranking 2021

• Published on November 25, 2021
• by Kashyap Raibagi

With the analytics industry now an integral part of the economy, there are scores of data science programmes in India that are being added by academic institutions. However, it can become confusing for students to decide on what courses best suit their needs. Hence, Analytics India Magazine surveyed to rank the Programmes in Data Science or Analytics in India. AIM has been coming out with these rankings for the last 8 years. The ranking outcomes will result from this survey and extensive research and discussions with the participating institutes. This report enlists the top Postgraduate Programmes for Data Sciences in India for the year 2021.

This year we have released just one ranking for all post-graduate level programs, irrespective of their mode of delivery. More than 60 programs participated in the ranking out of which 44 made it through.

These courses offer value in different ways to students, who can apply to them depending on what they want to learn and their career. A good course has high and well-balanced scores across all the parameters, making it to the top of the ranking. These rankings will help students identify the right course for them.

The report is helpful for institutes offering these programmes to understand where they stand compared to other courses and identify areas of improvement. It can also be used by the policymakers in public and private organisations to get an idea of the progress the Data Science education industry has made and then help bring changes accordingly. 

For previous year’s rankings, visit here .

Analytics India Magazine considered five different parameters for computing the ranking of Analytics or Data Science Programs — Certification Value, Return on Investment, Program Success, Teaching & Curriculum, and Student Engagement .

To determine this year’s Academic Rankings for Postgraduate Programmers in India, we derived an overall index. The index was calculated using the average score of five sub-indices (based on the aforementioned parameters). The sub-indices themselves were calculated based on the scores given to the answers (of the survey questions) asked by AIM using uniform evaluation criteria. These scores were normalised on a scale from 0 to 1 before the average for the sub-indices was taken. Outliers were capped. The hierarchy to calculate the overall index can be seen in the chart below.

No fee was charged for participation in the survey, and the participation was voluntary. The questions were answered by the institutes using a Google Form. We received a total of 62 responses , of which 44 with the highest overall index have been presented in this report. Others had to be left out due to answers that were incomplete or could not be scored according to the evaluation criteria.

Below we discuss the results of the analysis and present the top-ranking programmes across the different sub-indices and the overall index. 

Overall Index

All of the postgraduate courses listed have value to offer for the students who enrol in them. These are some of the top courses in the country that can help you set off your career in Data Science. Different courses offer different values, while some do well across all the parameters. This gives them a high overall index and brings them to the top of the table.

A balanced score across all the parameters shows a holistic approach taken by the institutes to ensure the best learning experience and career progression for their students.

According to our analysis, the PGP in Data Science with ML and AI by Praxis Business School scores the overall highest index with 0.73. It performs well across all the sub-indices. The course is a full-time Postgraduate Program that is taught live on-campus. Praxis as an institute has made quite a name for itself as a private institution, and its programs are highly regarded by recruiters. This was also the first program exclusively in data science to be launched in India. This gives it a score of 0.93 in the Certification Value sub-index.

The PGP in Computational Data Science offered by the International School Of Engineering (INSOFE) comes in second place with an overall index score of 0.72. The program has shown a great return on investment (with a score of 0.94). This is also reflected in the Program Success, scoring the highest within the sub-index (0.98).

T A Pai Management Institute or TAPMI’s Post Graduate Certificate Program in Leadership through Analytics and Decision Sciences delivered in collaboration with Mu Sigma is well-known for its Teaching & Curriculum (0.85). Several classroom sessions taught by a wide range of in-house and visiting faculty are followed by working on live projects in Mu Sigma that makes students industry-ready.

In the fourth position, we have Executive PGP in Data Science offered by upGrad with a score of 0.69. The program has a high score in Program Success (0.90) and RoI (0.83), ranking 4th and 5th in the respective sub-indices.

The PGP in Data Science offered by Simplilearn makes it to the fifth rank this year with a score of 0.68. The program has seen a total of 14 batches that it has completed with around 1400 students enrolled for it, with a Program Success sub-index score of 0.76.

The other programs to make in the top 10 include PGP in Data Science & Business Analytics by Great Learning and the PGDM – Big Data Analytics by the Goa Institute of Management (GIM), scoring 0.67 and 0.66, respectively.

These two programs are followed by PGCP in Data Science and Machine Learning offered by Times TSW, MBA in Business Analytics offered by REVA Academy, and the dual degree course MBA in Decision Science and Analytics & MS in Business Analytics and Information Management offered by the School of Business Management at NMIMS University in association with Purdue University.

Certification Value

Formal education through well-recognised institutions is one of the most important methods of filtration when enterprises are looking to hire candidates. Here, not only does the brand of the college or the university it is affiliated will matter, but the way the program is conducted is also considered. For example, organisations tend to prefer students who have studied their course on-campus in live classrooms than students who have studied online in part-time courses. Also, different program parameters like the duration, exams, and internships differ based on the certification a student is entitled to upon completion. In this section, we will analyse how different programs fared in the Certification Value sub-index.

The dual degree program of MBA Decision Science & Analytics and MS in Business Analytics & Information Management ranks highest in the Certification Value sub-index with a score of 0.99. The course is full-time and on-campus that offers a Masters degree upon completion. In addition, the students get to study in the School of Business Management at NMIMS and the Krannert School of Management at Purdue University.

The Post Graduate Program in Data Science & Business Analytics offered by Great Learning scores second-highest on Certification Value (0.98). The course is a Full-time on-campus and Masters level program. Not only is the program affiliated with the University of Texas (Austin), Great Learning has also made a significant name for itself. It is regarded highly by recruiters in India, with their students scaling up fast within the organisations.

In third place with a score of 0.93 for its Certification Value is the Post Graduate Program in Data Science with ML and AI offered by Praxis Business School. This is a full-time program that is taught live on campus. Located in Kolkata and Bangalore, Praxis Business School is regarded as one of the best private B-schools in India.

The next two courses with the highest Certification Value sub-index score of 0.88 each are MBA (Data Science and Data Analytics) and MBA (Business Analytics) offered by the Symbiosis Centre for Information Technology and Symbiosis Centre for Management and Human Resource Development. Both of these courses are conducted live on-campus and are full-time Masters-level programmes. The Symbiosis International Deemed University has consistently ranked highly among the top B-schools in India.

The MSc in Data Science course offered by the Pune Campus of Christ University and the M. Tech Data Science (Business Analytics) by NMIMS University rank 6th and 7th in Certification Value with 0.86 and 0.85, respectively.

The other three courses to make it in the top 10 include Post Graduate Program in Big Data Analytics (0.83) offered by the autonomous St. Joseph’s College in Bangalore, Master of Artificial Intelligence in Business (MAIB) (0.83) offered by SP Jain School of Global Management, and M. Tech Artificial Intelligence (0.80) by NMIMS University.

Return On Investment

While Data Scientists or Analytics professionals are in great demand, Data Science education is expensive. The institutes providing these courses also need considerable investment in terms of faculty and infrastructure, and at the same time, these courses need to be affordable to provide equal opportunity for everyone. Hence, return on investment (RoI) is important to consider. Placement opportunities in top enterprises with good salary packages are one of the main ways to identify courses providing good RoI. This section highlights the courses with a high median package to course fee ratio, highest placement packages, and good placement ratios.

The MBA in Business Analytics offered by the REVA Academy for Excellence scores the highest in the RoI sub-index with 0.96. While the course costs more than five lakhs, the median salary package for graduates placed through the program get a median salary of around 30 lakhs.

INSOFE’s Post Graduate Program in Computational Data Science ranks 2nd in the RoI subindex with a score of 0.94. The course fees are 4.45 lakh when the median salary from its placements is around 12 lakhs. The course, however, has a slightly lower placement ratio, with only 80% of the eligible students from the previous batch getting placed.

WileyNXT, in association with IIM Lucknow or IIM Roorkee, runs four programs, all of which make it to the top 10 in the RoI sub-index. In the third position is their Executive Program in AI for Business with a score of 0.91. While the course costs somewhere around 1.5 lakhs, the alumni of their course have a package between 7 lakhs to 50 lakhs. The institute only provides assistance when it comes to placements and 100% of their students have jobs after completing the course. Similarly, in the fourth position is their Executive Program in Strategic HR (0.86), previously known as Executive Program in Talent Analytics and Human Resource Management. It earns graduates a salary ranging between 13 to 107 lakhs.

With a 0.83 score in the RoI, the Executive Post Graduate Programme in Data Science offered by upGrad stands at the 5th position within the sub-index. While the course costs three lakhs, leading to an average placement offer of only 7.2 lakhs per annum, some students have seen pretty high placement offers.

The upGrad course is followed by the other two WileyNXT courses with almost identical scores of 0.79. One of them is conducted in affiliation with IIT Roorkee Lucknow. This Post Graduate Certification Program in AI for BFSI leads to its graduates earning between 10 lakh and 42 lakh after paying a fee of around 1.25 lakhs. The other is an Executive Program in Data-Driven Product Management . The salary of these alumni ranges somewhere between 16 to 30 lakh for a fee of 1.9 lakhs.

Finally, the Edvancer’s Advance Certification Programme in AI & ML in association with IIT Kanpur and the MSc Data Science offered by the Pune campus of Christ University score 0.76 and 0.69, respectively.

Programme Success

A program’s success can help prospective or interested students to know whether it has worked for students before. The number of batches conducted, and the number of students who graduated as a part of it can indicate the program’s success. In this section, we will analyse how successful the programs have been since their inception.

INSOFE’s PGP in Computational Data Science ranks the highest in Program Success with a score of 0.98. The program has successfully conducted almost 100 batches for which more than 3800 students have enrolled, of which 3500 have completed the program. The program has also successfully made several collaborations with different institutions and companies that can benefit from it. Students who opt for this program have the option to transfer credits for 11 Master’s programs with top-ranked universities and gain lateral entry into 2nd sem directly.

In the second position comes Intellipaat’s course Masters in Data Science (0.95). The certification program has completed more than 435 batches. Around 17,400 students have enrolled on this program, 70% of whom have graduated.

The PGP in Data Science & Business Analytics offered by Great Learning also scores very well (0.93) in the Program Success to rank third within the sub-index. With almost 150 batches now conducted, the program has been completed by more than 7000 students. These students constitute around a third of the total enrolled, which shows a lower completion rate.

With a score of 0.90, upGrad stands 4th in the subindex for its Executive Post Graduate Programme in Data Science . The online course has completed 24 batches graduating more than 7500 students. It has collaborated with The Math Company that benefit its students.

At fifth, we have the Praxis Business School for its Post Graduate Program in Data Science with ML and AI with a score of 0.83. The course has completed 24 batches, for which more than 800 students have enrolled. The course also has a high completion rate of 83%.

Simplilearn’s Postgraduate Program in Data Science and Ivy Professional School’s Diploma in Data Science, AI, ML and Big Data come in at the sixth and seventh positions, respectively, within the sub-index with a score of 0.76 and 0.72.

This is followed by the PG Program in Data Science offered by Edvancer (0.70), Post Graduate Certificate Program in Data Science and Machine Learning offered by Times TSW (0.68), and Post Graduate Program in Data Analytics by Simplilearn (0.67).

Teaching & Curriculum

Faculty is one of the most important aspects of a course. They not only influence how the course is taught but also encourage and direct students to the right career path. At the same time, curriculums decide what the students will learn. It is important to build courses that prepare students to work in actual data science teams. While classroom sessions and exams can build their knowledge, capstone projects and internships can help them prepare for working in the industry. In this section, we will analyse the Teaching & Curriculum aspects of the programs.

The dual degree MBA in Decision Science and Analytics & MS in Business Analytics and Information Management offered by NMIMS’ School of Business Management in collaboration with Krannert School of Management, Purdue University ranks the highest in Teaching & Curriculum with a sub-index score of 0.93. The programme has a good mix of teachers coming from academic backgrounds and industry experience teaching different subjects. They have hired around 34 teachers for the program, of which 16 have a PhD and 12 with industry experience of more than five years.

In second place with a score of 0.90 comes Goa Institute of Management’s 2-year PGDM in Big Data Analytics . There is a faculty of 26 teachers for the programme, 22 of which have PhD. It also has a large visiting faculty of almost 28 professionals and academics that come to teach. The students have to go through more than 960 hours of training, appear for several exams and complete multiple Capstone projects. Internships are also a big part of the course that helps students get work experience.

The third place is the Post Graduate Certificate Program in Leadership through Analytics and Decision Sciences offered by TAPMI, scoring 0.85 within the sub-index. Around 38 teachers at the institute are involved in teaching the course, 21 of which have a PhD and 16 have work experience greater than five years. The course, however, has only one visiting faculty. The course is 11-months long, with students needing 960 hours of studying.

Fourth and fifth place in the Teaching & Curriculum both offered by Symbiosis. One is the MBA in Business Analytics (0.83) offered by Symbiosis Centre for Management and Human Resource Development. The course has dedicated a faculty of 21 full-time teachers and 21 visiting faculty. Of the full-time staff, 18 of them have a PhD, and ten have work experience of more than five years. Similarly, the fifth-place course by the Symbiosis Centre of Information Technology of MBA Data Science and Data Analytics (0.79) has 19 full-time teachers (14 with a PhD and four with 5+ years work experience) and 16 visiting faculty. Both these courses run for two years and need almost 1500 learning hours to be put in by the students, along with exams, internships, and capstone projects.

Simplilearn’s Post Graduate Program in Data Science ranks 6th in the Teaching & Curriculum sub-index with a score of 0.76. The course has a faculty of 16 teachers, all of whom have work experience of greater than five years. However, only four of them have a PhD. The visiting faculty includes 15 teachers from some of the best institutes and organisations across the world.

Scoring 0.73 each, Christ University’s (Pune Campus) MSc in Data Science and Welingkar Institute’s Post Graduate Diploma in Research & Business Analytics come in 7th and 8th place. Both are 2-year courses that need their students to complete around 1000 learning hours along with exams, internships, and capstone projects. However, the Welingkar course has a comparatively lower number of faculty dedicated to the course.

Finally, the Master of Artificial Intelligence in Business offered by SP Jain School of Global Management and the MBA in Business Analytics by REVA Academy for Corporate Excellence also come in the top 10, both with a score of 0.70.

Student Engagement

While the number of students enrolled in the program or the ones that completed the course is an important indicator of how successful the program is, it is also important to consider how students engage with it. Attendance is not just about the student’s willingness to learn but is also indicative of how the program is conducted to keep the student’s attention. Secondly, it is also important to see how diverse the student enrollment is. The proportion of female students is indicative of this. Finally, it is also important to consider how students are enrolled in the program. The selection criteria for these students can help understand the efforts the program makes in curating a batch. This section analyses how good the programs have been in terms of engaging the enrolled students.

Praxis Business School’s Post Graduate Program in Data Engineering scores the highest student engagement score (0.87) by a considerable margin. Students have to go through an interview process, and their scores on existing exams are also considered. They have an attendance rate of 97% in their current batch. At the same time, almost two in five (79%) students in the current batch are women, indicating a high female representation.

In the second place, we have Goa Institute of Management’s PGDM in Big Data Analytics (0.79). The course has an entrance exam that is followed by an interview. The institute also considers marks from existing exams before admitting students. The program also has a very high attendance rate at 96%, and more than two in five (42%) of the students from the current batch are female.

Coming third in the sub-index is NMIMS University’s M. Tech Artificial Intelligence with a score of 0.75. Students who want to attend the course have to go through entrance exams and interview processes. Marks from existing exams are also considered. They have a 99% attendance rate in the current batch and a 40% female representation.

M. Tech in Data Sciences offered by Alliance University and the PGCP in Leadership through Analytics and Decision Sciences by TAPMI both score 0.73 to come in at 4th and 5th in the Student Engagement sub-index. Alliance University also has an entrance exam for the program. The students are screened for cutoffs in existing exams and have to undergo an interview process for both courses. Their current batches have a high attendance rate of 95%. However, with 38% and 21% of the students female, there is a scope for improvement in terms of representation.

Welingkar’s Post Graduate Diploma in Research & Business Analytics comes in at 6th with a score of 0.71. Students have to go through entrance exams and interview processes and be screened for their marks in existing competitive exams. The program has a comparatively lower attendance rate at 80%. But it has a perfect 50-50 representation of male and female students in the course.

With a score of 0.70 each, St. Joseph’s Post Graduate Program in Big Data Analytics , Simplilearn’s Post Graduate Program in Data Analytics , and NMIMS University’s M. Tech Data Science (Business Analytics) come in at 7th, 8th, and 9th position. Finally, we have Times TSW’s Post Graduate Certificate Program in Data Science and Machine Learning with a score of 0.69.

This report enlists the top Data Science Postgraduate Programs in India to give a holistic view of the Analytics education landscape in India. It quantifies how good these programmes are based on different parameters. This report can help students and professionals interested in a career in Data Science choose the right course for them.

Institutes across India have come up with many Data Science courses. They are trying to ensure the best quality education to help students set their journeys in this dynamic industry. Different courses offer different things, and students should opt for them depending on what is most important to them and their career stage. While for students just starting their professional careers, a program with a higher certificate value might be important. On the other hand, a mid-career professional might choose a program that offers the highest Return on Investment since that is the most important thing. All the courses listed in the report are some of the best courses offered in the country, and the decision to apply for them solely depends on what the individual aims to achieve.

You can read the entire report here.

Access all our open Survey & Awards Nomination forms in one place

Kashyap Raibagi

Top Under-graduate Data Science Programmes In India – AIM Ranking 2021

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INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI

Mehta Family School of Data Science & Artificial Intelligence

Data Science and Artificial Intelligence @ IIT Guwahati

• Conducting research and development in cutting-edge areas in DS & AI
• Building and nurturing DS & AI talent to tackle challenging problems

Recent Notifications

Recent seminars, selected publications, recent highlights.

Algorithm-based prevention and reduction of cancer health disparity for data-disadvantaged population

The long-term cumulative data disadvantage of some groups is a critical barrier to developing racially unbiased machine learning models. To overcome this barrier, the performance of machine learning models can be improved using transfer learning for data-disadvantaged groups to develop racially unbiased models. With her expertise, Teena Sharma aims to make significant contributions to this field by answering some of the pressing questions. Know more here .

Marching ahead to create the 6G THz Testbed with Orbital Angular Momentum(OAM) & Multiplexing

Ratnajit Bhattacharjee's research in RF, facilitated by a consortium consisting of SAMEER, IIT Madras, IIT Guwahati, and IIT Patna, is driving India's efforts towards the development of 6G technology. The advancement of 6G is anticipated to enhance the progress of machine learning and artificial intelligence by enabling faster data transfer in IoT applications. Know more here .

Talk Series on Chat about Artificial Intelligence (CHAI)

CHAI revolves around engaging discussions about comprehending intelligence, both natural and artificial, and brainstorming its implications for applications in science and engineering. The members of the School come together whenever a speaker is arranged, creating an environment where we listen, exchange ideas, and (often) also enjoy a cup of chai together. Know more here .

Students making us proud

Our UG student members (2021-2025 Batch) - Aditya Gupta, Anant Kacholia, Aryan Lath, Devansh Bhardwaj, Nischay Nilabh, Subhash Patel, Varun Nagpal and Nityam Pareek represented IIT Guwahati in the Inter-IIT Technical Meet . The group, with their tenacity to think beyond the box about complex problem statements, won two gold medals and one bronze medal, making the institute proud. Besides this, Anant Kacholia with his two mates , also participated in Nobias Finance Investment Challenge 2023 and bagged the First prize of 5000 USD!

Listening to body sounds: Analyzing respiratory sound signals for design of AI-based disease screening methodologies

Thanks to improved non-invasive and easy capture of bodysounds using microphones and developments in data analysis techniques, acoustic epidemiology aided with artificial intelligence (AI) is gaining attention. In this project, Neeraj Sharma's group will focus on capture of lung sounds, and explore systematic analysis of these sound signals using approaches in signal processing and machine learning. The goal is to develop methods which allow detecting signatures in the sound signals which are associated with specific kinds of respiratory diseases. Know more about a related work on COVID-19 pursued by the group here

School of DS&AI Welcomes 2022 Batch of BTech Students, Expanding Capacity and Igniting a Quest for Impact

We are thrilled to extend a warm welcome to the incoming batch of BTech students for the year 2022 at the School of DS&AI. These students will join us as we collectively strive to explore deeper and create a positive impact on our world. The new students have come from various regions across India, having demonstrated their exceptional talents by excelling in the competitive IIT JEE (All India examination). To familiarize them with the School and its programs, an orientation meet was organized on 27th October 2022. It is worth mentioning that this year, the School has expanded its intake capacity from twenty students in 2021 to thirty students, enabling us to accommodate more aspiring individuals.

Reinforcement learning for mobile edge computing system

In an Internet of Things (IoT) based network, tasks arriving at individual nodes can be processed in-device or at a local Mobile Edge Computing (MEC) server. This project, led by Arghyadip Roy , focuses on the optimal resource allocation problem for tasks arriving in an MEC-based IoT network. To address the high complexities of achieving optimality, the aim is to develop low-complexity task scheduling schemes. Additionally, reinforcement learning (RL) based approaches will be developed that can learn the optimal policy by interacting with the environment. The performance of the RL-based schemes will be evaluated in system-level simulators. More details can be found in this paper on a related work of ours, and a presentation on the same is available here .

Analysis of facial tissue movements using AI

The eye and facial movements convey subtle information about the mental state (e.g., attention, intention, emotion) and physical state (e.g., age, health, fatigue) of a person. These movements, which generate facial expressions, are carefully scrutinized by humans in social settings. Debanga Raj Neog's lab is focussing on developing Artificial Intelligence (AI)-based systems for measuring, modeling, and animating eye gaze and facial tissue deformations for applications in healthcare and computer animation. The idea is to use high frame rate vision systems to capture human faces, and apply data-driven approaches to analyze and model facial expressions. In the healthcare sector, facial movement analysis can be used to develop tools for rapid assessments of mental health and to build patient-computer interaction systems. In computer graphics, it can help in creating real-time and hyper-realistic computer-generated animations of human eyes and faces in creating convincing and interactive animation characters. Know more here .

Modeling and prediction of nearly periodic phenomena

A short text description - Coming soon!

We continue to design and offer new (advance) courses

We know teaching and learning feed each other. Our Faculty have designed specialized courses in DS&AI which they enjoy to teach, and also help student gain the depth and breadth in this exciting field. Know more here .

Campus gets another supercomputer

Named "Param Kamrup" , this is a 838 teraFLOPS super computer with 107 CPU nodes, 10 GPU nodes, 9 high memory nodes, 740 CPU cores, and several CUDA cores. Our data scientists are getting ready to crunch numbers with these machines!.

DS&AI at IIT Guwahati brings together faculty members specializing in diverse areas of Data Science and AI. We boast a highly skilled group of researchers who are dedicated to crafting innovative solutions for complex challenges encountered in India and worldwide.

Learn with Us

In the lively campus of IIT Guwahati, our students collaborate closely with faculty, engaging in the pursuit of knowledge and crafting solutions to unravel the "whys and why nots" of various challenges.

Partner with Us

Founded in 2021, we serve as the gateway to North-East India. We are open to collaboration with you as well. Our vision includes partnering with prominent names in AI research, such as technical companies, non-profits, and other universities, to achieve impactful outcomes together.

We're using DS&AI to solve challenging problems, but we can't do it without the best people and resources. Engage with us.

• COVID-19 Updates

Ph.D. in Data Science and Technology |

With data being recognized as the new oil for organization, it provides large scope for the research scholars to explore and propose new digital models that will provide insights for the organisations to transform their businesses. The most important aspect of any computer application and framework is the manner in which both structured and unstructured data are stored, retrieved and analysed to better predict the outcomes.

Data Science has evolved as cross-functional management science that encompasses designs and use of algorithms, employing systematic and scientific methods to extract knowledge, create new models for effective and efficient decision-making. Information is recognized as a Business Resource (IaBR) that supports all the stages of decision-making.While automation and digitization of routine processes has matured over the years, the businesses are exploring new avenues for transforming their business processes by leveraging the digital technologies.

Businesses have to either foster Technology-Enabled Disruptive innovations or will gradually perish is the new mantra for survival.Big Data and Machine Learning applications, Business Intelligence and Artificial Intelligence, Data mining and Visualisation, Internet of Things and Embedded Systems are the new terms that an organisation wants to get associated with and are willing to encourage research and adopt new solutions in these areas. Digitisation leading to Digitalisation is the key strategy for the future of businesses. Thus, some of the focus areas for scholars could be in line with: Information Technology enabled cross-functional applications and Decision Making Big Data Analytics, IoT, Web-based applications and analytics Networking, Technology and Framework adoption, E-Services, Cyber Security Digital interventions and its impact on cross-functional processes Diffusion, M-Commerce, E-Learning, E-Governance, ICT applications, Digital Transformation

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• Programme Code ST1753
• Course Type Ph.D.
• Mode of study Regular
• Campus Vidyavihar - Mumbai
• Institute K J Somaiya Institute of Management

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MS & PhD

IIT Palakkad offers two research programmes, Master of Science (2 years) and PhD (5 Years) in the area of Data Science, which is organised by the department. It has a vibrant research community with scholars and faculty, working on various aspects of data science, including machine learning, data mining, big data analytics, and computer vision. We focus on developing advanced algorithms and prototypes that are used to tackle challenging real- world problems in various domains such as healthcare, agriculture, and transportation. We also collaborate with industry partners and other academic institutions to bring their cutting-edge research to bear on practical applications. 

Our research community broadly covers the following core research areas:

• AI and Machine learning: Kernel Learning, Multiview Learning, Robust Optimization and Convex Optimization for Large Data, Anomaly Detection in Time Series, Privacy-aware Learning, Bayesian Model.  
• Systems for AI: Computer Vision, Architecture for Deep Learning, Energy-efficient and High-performance Systems for Multimedia Applications, Energy-aware Algorithms for Signal Processing to efficient architecture design,  Low-power VLSI circuit implementation.  
• Information Retrieval and Natural Language Processing: Harvesting Knowledge from Text and Web Tables; Knowledge Base Curation,  Question-Answering, Building Smart Indices for Efficient Similarity Search.  
• Information Theory and Statistics: Statistical Learning and Inference, Federated Learning, Mathematical Statistics.

Research Admission July 2023 is open now. Please visit the portal to apply. 

Deadline: 30th April

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PhD Admissions

Phd admissions july 2024, phd admissions january 2024.

May 20, 2023: Candidates shortlisted for written test has been informed though their regsitered email. Please check your spam folder also.

May 09, 2023: Candidates shortlisted based on the written test performance will be called for interviews at IITH campus. The interviews will be held on the 9th June 2023. Requests for online interviews will not be considered.

May 09, 2023: The online written test for the PhD program will be held on 27th May 2023, from 10 am. Details about the modalities of the test will be informed to the shortlisted candidates by email. Shortlisting is currently under progress, and is expected to be completed by early next week.

PhD Admissions July 2023

The Department of AI at IIT Hyderabad helps in creating a complete ecosystem for AI Academics and Research at IIT Hyderabad. The department offers B.Tech, M.Tech. and PhD programs (full time and part time). The emergence of the department is the consequence of the heavy demand from the industry on artificial intelligence and data analytics, and the need to tackle the many fundamental and foundational research problems arising in a rapidly evolving field. The department's mission is to

• Train students to have a sound understanding of the fundamentals of the theory and practise of Artificial Intelligence and Machine Learning.
• Enable students to become leaders in the industry and academia nationally and internationally
• Meet the pressing demands of the nation in the areas of Artificial Intelligence and Machine Learning.

The Department of Artificial Intelligence has a sizable number of highly dedicated and dynamic faculty members, with a wide variety of expertise. Faculty publishes regularly in top AI conferences and journals such as NeurIPS, ICML, AAAI, IJCAI, CVPR, ICCV, ACL, EMNLP, AAMAS, JMLR, TIP, TACL etc. Currently there are 29 faculty members affiliated with the AI department. Candidates can discover the profiles and teaching/research areas of different faculty members by visiting Faculty Profiles

The PhD students will be provided with excellent laboratory facilities that they can access at any time. The laboratories are equipped with state-of-the-art facilities including software and hardware (including high-end DGX servers and other GPU servers).

The Department of AI seeks talented and dedicated PhD students to develop highly skilled human resources who can contribute to modern and cutting edge research in AI.

Eligibility Criteria for Application to the PhD program:

The Eligibility criteria for regular PhD program is MTech/Equivalent Degree in CS/ECE/EE or related areas in Artificial Intelligence. The applicant must have already earned the Master's degree, or should at least be in the final year of the respective pro-gram. In the latter case, it would be assumed that the candidate will be able to complete the degree by the time of admission into the PhD program. Candidates with MSc/MCA/equivalent PG degree with an EMDS at IIT-H may apply for Regular PhD program.

The Department of AI considers Direct-PhD admission , where the eligibility criteria is BTech/BE/MCA/MSc/Equivalent Degree in any engineering discipline or Maths, and have a valid GATE score in CS/EC/EE/MA/ST. Candidate with BTech/BE/MCA/MSc/Equivalent Degree in any engineering discipline or Maths from any Centrally Funded Technological Institutes (CFTI), with CGPA 9 or above can apply without a valid GATE score (For candidates from IITs/NITs/IIITs this is relaxed to CGPA 8 or above).

The Department of AI also considers Direct-Phd admission , where the eligibility criteria is BTech/BE/MCA/MSc/Equivalent Degree in any engineering discipline or Maths, and have a valid GATE score in CS/EC/EE/MA/ST. Candidate with B.Tech/M.Sc in any engineering discipline or Maths from any Indian Institute of Technology (IIT), with CGPA 8 or above can apply without a valid GATE score

Department also admit students to the part time PhD program . Part time PhD program have the same eligibility criteria listed above and in addition the candidate must be employed with a relevant employer at the time of application and admission.

For admission to the program, there will be a preliminary shortlisting depending upon the academic background. Candidates who satisfy the shortlisting criteria need to appear for a written test and/or an interview. The shortlisting criteria could be higher than the eligibility criteria. In addition, the department also reserves the right to set any cut off criteria for shortlisting the candidates and not to select anybody if no appropriate candidates are found.

IIT Hyderabad has a centralized online application portal for the PhD admission. Candidates are requested to visit IITH PHD Admissions for the application format and the submission link. Candidates applying for any of the PhD program are requested to submit their application through the portal. For other related information, such as last date of application, shortlist announcement, written test and interview dates, please visit https://ai.iith.ac.in/phd-admissions.html

For any query, kindly write to​ ​[email protected]

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BITS Pilani is a Deemed to be University, offering on-campus programs to more than 18,500 students across its campuses in Pilani, Goa, Hyderabad, Mumbai and Dubai.It has been recognized as an Institute of Eminence by the Ministry of Education, Government of India in 2020.

QS World University Subject Rankings 2024 has ranked BITS Pilani globally at

• 101-150 in Pharmacy and Pharmacology
• 301-350 in 4 subjects namely, EEE, Computer Science, Mechanical and Chemical Engineering
• 451-500 in 3 subjects, namely, Mathematics, Business & management Studies and Physics & Astronomy
• 501-550 in Chemistry

In ǪS Asia University Rankings 2024, BITS has been ranked 215th in Asia and at 22nd in India. Further, BITS Pilani has been ranked among the top 300 in ǪS World University Graduate Employability Rankings 2022 and within top 6 in India.

Having pioneered several curricular and pedagogic attributes, BITS Pilani has a vision to be amongst the top research-led Institutes in the country. The qualities of innovation, enterprise, commitment to excellence, adherence to merit, and transparency, have characterized the Institute during its inexorable march to eminence.

The Institute has secured over Rs 398 crores as external research funding in the last 5 years. State of the art facilities have been developed to support cutting edge research, led by students and about 930 faculty members, leading to a Scopus h-index of 156, with 221 patents filed so far, and 41 patents granted. Currently, there are 14 BITSian Unicorns and 1 Decacorn. There are over 7500 BITSian founders and co-founders of enterprises.

Doctoral Programme (Ph.D.)

List of Candidates shortlisted for Ph.D. Admission Test and/or Interview is now available

Admissions portal open 01st march 2024.

Please click here for more information.

List of Candidates shortlisted for Ph.D. Admission Test and/or Interview is now available.

• CLICK HERE to know the Result.

Department preference with regard to the full-time and part-time Ph.D student admission is given in the table below.

Yes – A Department intends to admit students under the specified mode. No – A Department does not intend to admit students under the specified mode.

Minimum Eligibility Qualifications

ME / MTech / MPharm / MBA / MPhil (minimum of 60% aggregate)* MSc/BE/BPharm or an equivalent degree (minimum of 60% aggregate)* For admission into Humanities and Social Sciences, MA degree (minimum of 55% aggregate)* For part-time applicants, a minimum of one-year experience in the related field of study is required

[*In the Qualifying Degree examination]

In addition, Departments may set specific admission criteria for shortlisting. Meeting the minimum eligibility qualifications does not guarantee admission into the PhD program. Shortlisted candidates will have to appear for an admission test, which may comprise a written exam and/or interview. Information on specific Departments and related research activities is available on the Department homepage of respective campuses.

Full-time students

Preferably individuals who would like to pursue PhD in-house, residing on campus.

Part-time students

Preferably individuals who are working in organizations providing basic facilities and an environment for research.

Financial Assistance

Full-time PhD students admitted into the PhD program are eligible to be considered for an Institute fellowship of Rs. 34,000 or Rs. 37,000 per month in the first year based on their qualifications at the time of admission. Students admitted with M.E./M.Tech./M.Pharm./MBA/M.Phil. or an equivalent Degree are eligible to receive an Institute fellowship of Rs. 37,000/-. Students admitted with M.Sc./B.E./B.Pharm. or an equivalent degree are eligible to receive an Institute fellowship of Rs. 34,000/-. These students on successful completion of coursework will receive Rs. 37,000/- from the Semester following the one in which the course work was completed Higher fellowship may be made available in subsequent years. Consideration for Institute fellowship will be as per Institute norms. It will be obligatory on the part of every admitted full time student to undertake 8 hours (per week) of work as assigned to him/her by the institute.

Important Dates

The Institute reserves the right to change the above deadlines. Candidates will be informed in advance should there be such a change.

Department Brochures

Pilani campus – biological sciences, pilani campus – chemistry, pilani campus – chemical engineering, pilani campus – civil engineering, pilani campus – electrical & electronics engineering, pilani campus – humanities and social sciences, pilani campus – physics, pilani campus – mechanical engineering, goa campus – biological sciences, goa campus – chemistry, goa campus – computer sciences, goa campus – electrical & electronics engineering, goa campus – humanities and social sciences, goa campus – mathematics, goa campus – mechanical engineering, hyderabad campus – biological sciences, hyderabad campus – chemical engineering, hyderabad campus – chemistry, hyderabad campus – civil engineering, hyderabad campus – computer sciences, hyderabad campus – electrical & electronics engineering, hyderabad campus – humanities and social sciences, hyderabad campus – mathematics, hyderabad campus – mechanical engineering, hyderabad campus – pharmacy, top resources.

For Further Information Contact

Admissions office.

Birla Institute of Technology & Science, Pilani Campus, Pilani, Rajasthan 333031 (INDIA).

(Note : For any query you may contact through the above phone numbers on any working day from Office Hours : Monday to Friday 9AM - 1PM & 2PM - 5PM Saturday 9AM - 1PM)

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PhD in Data Science

• Updated on  
• Dec 6, 2023

If you’re interested in working independently in research fields after completing a master’s in mathematics, statistics , science, etc, then pursuing a PhD may be the right choice for you. It offers many reputed career choices along with satisfaction. The field is continuously growing and top companies Microsoft, Wipro, HCL, etc, are demanding data science graduates. So, read about PhD in Data Science to know about the course, its duration, after options, salary, top recruiting companies, and more.

This Blog Includes:

What is a phd in data science, eligibility criteria, list of top universities offering phd in data science abroad, universities offering phd in data science in india, researchers , college professors , senior data scientist, business analysts, machine learning professionals, average salary for phd graduates, top companies hiring data science graduates.

A PhD in Data Science gives students an edge and provides them with relevant knowledge in the fields like AI, Statistics, Machine Learning , Data Analysis, and the list goes on. Like all other PhD-level courses, it enables students to work independently in research fields and helps them apply both their practical and theoretical knowledge in data models.

Also Read: Fully-Funded PhD Programs

A PhD in Data Science has emerged as one of the leading courses as it enhances the career prospects of the candidates providing them with research and in-depth academic knowledge. Different universities have different specific criteria for admission that has to be met by the candidates. The basic eligibility requirements are given below:

• Candidates willing to pursue a PhD in Data Science and related courses must have a master’s degree in related fields like computer science, Statistics, Mathematics, etc
• Some universities have their own entrance exam for PhD level courses
• Marks scored by the candidate in related entrance examinations such as GATE, UGC-NET, CSIR-UGC-NET, etc are also considered for the admission process and these candidates are exempted from giving university entrance exams. But these candidates have to undertake a research skill assessment test. (Only valid for Indian Universities)
• Some colleges also take personal interviews and written tests in shortlisting candidates.
• English test scores of exams like IELTS / TOEFL etc (Only valid for foreign universities)
• Candidates require a set of documents like a 10th Marksheet, 12th Marksheet, Bachelor’s Degree & Marksheets, and Master’s Degree & Marksheet.

Book a FREE session with Leverage Live to ace your English proficiency tests like IELTS, TOEFL, PTE, and more!

When applying abroad it’s always wise to know your options beforehand! Sometimes choosing the right university for you might look like a daunting task.

The following are the top universities in India offering PhD in Data science:

Must Read: How to Write Acknowledgement for Dissertation?

Career Choice after PhD in Data Science

The following are the top career choices after PhD in Data Science:

Researchers conduct their research in an organized and systematic way. They are responsible for communicating their research honestly and ethically. Also, they transfer and exploit their knowledge for the betterment of employees, the environment, and society as a whole and also collaborate with others whenever necessary. 

A data science college professor is expected to design, develop and teach courses in the Data Science domain and related areas. Sometimes, they engage in exploring new methodologies and technologies through research. Also, they mentor and supervise students in their projects and internships too.

A senior data scientist engages in formulating, suggesting, and managing data-driven projects which are in favour of business interests. They also collate and clean data from various entities in order to help their junior data scientists . 

Business analysts help organizations in improving their processes and systems. They conduct research and analysis to solve business problems and introduce solutions to businesses and their clients. 

A machine learning professional is an expert in using data to train models. These models are used to automate processes like image classification, market forecasting, speech recognition etc. 

The average salary in Data Science after doing a PhD can range from Rs 70-75 Lakhs per annum. With more experience, it can be raised to Rs 1 Crore or more. Although it depends on what career path you are choosing and in which state or country you are employed.

Must Read: What is a PhD Stipend?

• Thomson Reuters 

Yes definitely! You can prove to be a leader in the field by doing a PhD in Data Science. And also, a PhD in Data Science also has a higher return on investment as compared to other data science master’s programs.

A PhD in Data Science takes around 4-5 years depending on the university and country you’re pursuing from.

Researcher, college professor, machine learning professional, senior data scientist, and business analyst are some of the positions you can opt for after completing your PhD in Data Science. 

We hope this blog helps you in understanding all the essential aspects of PhD in Data Science. Aiming to study a similar course or thinking of doing a PhD in another field? Sign up for your free 30 minutes of e-counselling with the Leverage Edu team now!

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Ph.D Data Science at IISER Pune Offline Course

Quick facts, fees details, course details.

The PhD programme at IISER Pune is a blend of classroom curriculum, mentoring under-graduate students along with a major research component. The research scholars are expected to complete at least 16 credits of coursework within the first two semesters followed by a comprehensive examination to assess the student’s candidacy for PhD. They must deliver a departmental seminar and undertake tutoring activities in at least three courses (theory and/or laboratory courses). In the first two years, the student will receive a Junior Research Fellowship (JRF). Upon the successful completion of the comprehensive examination and two years of JRF, the student will be eligible to receive a Senior Research Fellowship (SRF) for a maximum of another three years. The research progress of the student will be monitored on a yearly basis by a Research Advisory Committee (RAC) involving the thesis supervisor (Convener) and two other faculty members. Upon completion of satisfactory research work (as construed by the RAC), the research scholar will deliver a research seminar regarding their work before the submission of thesis. The submitted thesis will be evaluated by external examiners before the conduct of viva-voce. Successful open defense of the thesis will lead to award of PhD degree during the annual convocation.

Eligibility Criteria

1. Master's degree or a four-year Bachelor's degree like B.E., B.Tech, or equivalent in Mathematics, Statistics, Computer Science, or related branches.

For applicants from General/OBC/EWS category: Applicants must have a minimum of 60% marks in aggregate (overall percentage and not just in the majoring subject) or an equivalent CGPA.

For applicants from SC, ST or PwD category: Applicants must have a minimum of 55% marks in aggregate (overall percentage and not just in the majoring subject) or an equivalent CGPA.

Students whose final results in Master's or equivalent are yet to be declared can also apply. However, if selected, the offer for these students will be  provisional , subject to their fulfilling the above criteria  at the time of admission .

2. In addition to the above, the candidate  MUST  have at least one of the following qualifications:

a. Qualified a national level eligibility exam such as CSIR-JRF, UGC-JRF, DBT-JRF-A, DBT-BINC-JRF, JEST, NBHM, GATE, JGEEBILS, etc. The corresponding score / selection / award letter must be valid at least till 31 August 2023. b. INSPIRE-PhD fellowship

(Should be in possession of provisional selection letter at the time of interview). c. An integrated BS-MS dual degree from any of the IISERs with CGPA ≥ 8.0

For all the national level eligibility examinations which provide a common rank / score, the cut-off rank / score for shortlisting for the Interviews for the reserved categories shall be lowered to 1.25 times the General category rank / score.

Admission Details

Based on the application forms received, the above-listed criteria, and additional criteria set by the Department, applicants will be shortlisted for interviews. Shortlisted candidates will be screened for admission to the PhD programme through a rigorous evaluation process that includes an interview and other criteria set by a selection committee. The mere application or shortlisting does not guarantee admission into the PhD programme.

Other Popular Courses in this College

Other popular universities offering this course, sant gadge baba amravati university, amravati.

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Getting a PhD in Data Science: What You Need to Know

A PhD in data science prepares you for some of the most cutting-edge research in the field and can advance your career. But, whether you should pursue one depends on your own personal goals and resources. Learn more inside.

A Doctor of Philosophy (PhD) is the highest degree that a professional can obtain in the field of data science. Focused primarily on equipping degree holders with the skills and knowledge required to conduct original research, a PhD prepares degree holders for advanced professional positions in both industry and academia. 

But, the path to obtaining a PhD is filled with many years of potentially costly study that can be discouraging to those looking for rapid career progression. Before jumping into a doctoral program, then, it’s important to define what your goals are and how a PhD may (or may not) fit into them. 

In this article, you’ll learn more about PhDs in data science, the different factors you should consider before joining one, and types of programs to consider. At the end, you’ll also find some suggested online courses to help you get started today. 

PhD in Data Science: Overview 

A Doctor of Philosophy (PhD) is the terminal degree in the field of data science, meaning it is the highest possible degree that can be obtained in the subject. Holding a PhD in data science, consequently, signals your mastery and knowledge of the field to both potential employers and fellow professionals. 

At a glance, here’s what you should know about a Data Science PhD: 

PhD vs. Master’s Degree in Data Science

There are two graduate degrees in the field of data science: a master’s in Data science and a PhD in Data Science. While both of these degrees can have a beneficial impact on your job prospects, they also have key differences that might impact which one is better for you. 

A Master’s in Data Science is a graduate degree between a bachelor’s and PhD, which usually takes between one and two years to complete. A master’s degree expands on what was learned in undergraduate school through more advanced courses in topics such as machine learning, data analytics, and statistics. Often, a master’s student in data science also pursues original research and completes a capstone project, which highlights what they learned in their program.

A PhD in Data Science is a research degree that typically takes four to five years to complete but can take longer depending on a range of personal factors. In addition to taking more advanced courses, PhD candidates devote a significant amount of time to teaching and conducting dissertation research with the intent of advancing the field. At the conclusion of their doctoral program, a PhD holder in Data Science will complete a dissertation representing a significant contribution to the field. 

Typically, bachelor’s degree holders entering a PhD program are able to earn their master’s degree as a part of their doctoral program. Those entering a master’s program, however, will usually have to apply for a PhD program even if it’s in the same department. 

Skills and curriculum 

Every PhD program is unique with its own requirements and focus. Nonetheless, they do have similar features, such as course, credit, and teaching requirements. To help you get a better understanding of how a doctoral graduate program in data science might be, here’s an example curriculum from NYU [ 1 ]: 

Complete 72 credit hours while maintaining a cumulative grade point average of 3.0 (out of 4.0) each semester.

Core courses in topics like probability, statistics, machine learning, big data, inference, and research. 

39 credit hours for elective courses in such topics as deep learning, natural language processing, and computational cognitive modeling. 

Complete teaching requirements.

Pass a comprehensive exam. 

Pass the Depth Qualifying Exam (DQE) by May 15 of their fourth semester. 

Complete all steps for approval of their PhD dissertation. 

Is a PhD in Data Science worth it? 

A PhD can open doors to new career opportunities and boost your employment prospects. But, it can also take a lot of time and money to complete. Everyone’s personal and professional goals are different, so consider these things when deciding if you should pursue a PhD in Data Science:  

Cost and time

The amount of time and money it takes to complete a PhD are perhaps the most concrete considerations one makes when deciding whether or not they should pursue a doctoral degree. According to research conducted by Education Data Initiative, the average cost of a doctorate degree is $114,300 and takes roughly four to eight years to complete [ 2 ]. 

The exact amount of time and money you might spend obtaining your doctoral degree will depend on your own circumstances and program. Before applying for a doctoral degree, make sure to review each program’s graduation requirements and costs, so you have a clear understanding of what you’re getting into. 

Data Science PhD salary 

While there are no official statistics on the salary gains data scientist earn by getting a PhD, the median salary for all data scientists is much higher than the national average in the United States. According to the U.S. Bureau of Labor Statistics (BLS), for example, the median salary for data scientists was $100,910 as of May 2021 [ 3 ]. 

Typically, the entry-level degree to get a data science position is a bachelor’s degree, meaning that even just an undergraduate degree could help you land a job that earns a higher than average salary. Nonetheless, a PhD will likely prepare you for more advanced positions that could offer higher pay than less specialized roles. 

Data Science PhD programs 

There are several types of doctoral programs that you might consider if you would like to obtain a PhD in data science. These include: 

PhD in data science online

An online PhD program may appeal to individuals who are interested in a more flexible program that allows them to complete their coursework at their own pace. Often, online programs can also be cheaper than their in-person counterparts, though they often offer less opportunities for networking and mentorship. If you’re an independent, self-starter looking for a program that can fit into their already busy life, then you might consider an online PhD program. 

PhD in data science in-person

An in-person PhD program is a more traditional, educational method in which you attend classes on campus with your peers and instructors. In addition to providing doctoral-level instruction, you will also have more opportunities to network and gain more personalized instruction than you will likely encounter through online programs. In-person programs tend to be more expensive and inflexible than in-person ones.

If you prefer real-world instruction, networking opportunities, and a more rigid structure, then you might consider an in-person doctoral program. 

Alternatives 

As an alternative to a PhD program, you might also consider obtaining a master’s degree. While covering some of the same material as a doctoral program, a master’s usually takes much less time and money to complete.

If you’re motivated primarily by the desire to boost your chances of landing a job and gaining financial stability, then a master’s degree program might better help you achieve your goals.

Learn more about data science 

Whatever your educational goals, data science requires extensive knowledge and training to enter the profession. To prepare for your next career move, then, you might consider taking a flexible online course through Coursera. 

The University of Colorado Boulder’s Data Science Foundations: Data Structures and Algorithms Specialization teaches course takers how to design algorithms, create applications, and organize, store, and process data efficiently. Their online Master of Science in Data Science , meanwhile, teaches broadly applicable foundational skills alongside specialized competencies tailored to specific career paths in just two years of instruction. 

Article sources

NYU Center for Data Science. “ PhD in Data Science, Curriculum , https://cds.nyu.edu/phd-curriculum-info/.” Accessed September 27, 2022. 

Education Data Initiative. “ Average Cost of a Doctorate Degree ,  https://educationdata.org/average-cost-of-a-doctorate-degree.” Accessed September 27, 2022. 

US BLS. “ Occupational Outlook Handbook: Data Scientists , https://www.bls.gov/ooh/math/data-scientists.htm#tab-1.” Accessed September 27, 2022. 

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What about a PhD in Data Science in India? 

• June 12, 2023
• No Comments

If you want to pursue a PhD in Data Science, then you should first look at the eligibility criteria and the aspects involved with it. This will help you decide whether this path is right for you. 

Table of Content

1.  PhD in Data Science   2.  A PhD in Data Science Eligibility Criteria 3.  Is a PhD in Data Science Valuable in India?   4.  Can I opt for a Data Science PhD Online?   5 .  PhD in Data Science: Salary Options   6 . Part-Time PhD in Data Science   7 . Part-Time PhD in Data Science Eligibility Criteria 8 . Eligibility Criteria And The Aspects 9 . Why should someone pursue a PhD in Data Science?

PhD in Data Science  

A PhD in Data Science is a degree that many people pursue, especially those who want to make their mark on the world and shape it in their image. These days, you can study for this degree online or at universities like MIT or Stanford University. 

A PhD in Data Science Eligibility Criteria:  

To be eligible for admission into a PhD program at an accredited university. You must meet specific requirements, such as being a citizen of India or holding an F1 visa (i.e., student visa). If you do not fulfil these eligibility criteria. Then there are other ways around them: applying through transfer credits from other institutions as well as international students. Who have already graduated from top universities worldwide! 

To apply for a PhD program, you must have completed your master’s degree with a minimum of 70% or above. You must also submit your GRE score and transcripts from all universities you have attended.  

If you meet these requirements and wish to enrol as an international student. Then it may be possible for you to receive financial aid based upon financial need under certain circumstances; however, not all students qualify for this benefit due to their events such as family size/income level etc. 

Is a PhD in Data Science Valuable in India?  

Yes, it is. A PhD degree is one of the best for professionals who want to make a career out of data science. It is also one of the best options for getting a free master’s degree. However, if you are looking at this question as an Indian student and are wondering whether you should contact your PhD in data science started right now then let us answer your questions: 

Can I opt for a Data Science PhD Online?  

You can opt for a Data Science PhD online if you have: 

1. A busy schedule and cannot study full time 2. A family to care for or children who need your attention 

If any of the above apply to you. Then an online PhD in data science is the best option. 

PhD in Data Science: Salary Options  

When it comes to salary, the following factors play a role: 

1. Industry: The industry in which you work, and the nature of your job will determine your salary. For example, if you work in an IT company, your salary will be higher than. If you work for an educational institute or non-profit organisation.  2. School/university: Different universities offer different PhD programs with varying levels of funding and research opportunities. Those who study at top-rated universities earn more than those. Who look at lesser-known institutions. It’s essential that before applying for a PhD program. They know exactly what they’re getting into when they go through the selection process! 

Part-Time PhD in Data Science  

A Part-Time PhD in Data Science is a two-year (three years for part-time) full-time PhD program that allows students to earn their degrees part-time. The Part-Time PhD in Data Science Eligibility Criteria, Salary, India and more are covered here. 

Part-Time PhD in Data Science Eligibility Criteria:  

A candidate must be an Indian citizen who has passed 12th class with at least 50% marks from any recognised university; or has completed graduation from any institution which is equivalent to PhD level. Whichever comes first, or has completed MCA/MBA or other comparable graduate coursework program with minimum 60% marks as per university regulations; 

If you want to pursue a PhD, then you should first look at the eligibility criteria and the aspects involved with it.  

If you wish to pursue a PhD. Then you should first look at the eligibility criteria and the factors involved with it. 

• You must have completed your graduation from any college or university in India or abroad, with an overall GPA of at least 70% (on a scale of 0-100). 
• You must have secured admission into an accredited institution of higher learning (IITs, IIMs etc.) that offers PhD programs in Data Science. 
• It is also essential that you demonstrate exceptional academic performance through GRE/GMAT scores or any other standardised test such as CAT/MAT/MCQs etc., which can help you get admission into some top universities around India. 

Why should someone pursue a PhD in Data Science? Is it worth it?  

There are several compelling reasons why someone should consider opting for a data science program: 

• Increasing demand: Data science is a rapidly growing field with a high demand for skilled professionals. By pursuing a data science program, you can position yourself for numerous job opportunities in industries. Such as technology, finance, healthcare, marketing, and more. The demand for data scientists is expected to con technology, finance, healthcare, marketing, and more industries continue rising as organisations recognize the value of data-driven decision-making. 
• Lucrative career prospects: Data scientists are among the highest-paid professionals today. With a data science program, you can acquire the skills and knowledge needed to excel in this field, increasing your earning potential and job prospects. 
• Solving complex problems : Data science enables you to tackle complex business challenges by extracting valuable insights from vast amounts of data. Through a program, you’ll learn various techniques and tools to collect, analyse, and interpret data, empowering you to make informed decisions and solve critical problems in your organization. 
• Versatility and interdisciplinary skills: Data science programs typically cover a wide range of topics, including statistics, machine learning, data visualization, programming, and more. This interdisciplinary approach equips you with a diverse skill set, allowing you to work on different projects and collaborate with professionals from various backgrounds. 
• Driving innovation and growth : Data science plays a pivotal role in driving innovation and business growth. By harnessing the power of data, organisations can uncover patterns, trends, and insights that lead to enhanced products, improved processes, and better decision-making. With a data science program, you can contribute to the advancement and success of your organisation or even start your entrepreneurial venture.  
• Continuous learning and development: Data science is a dynamic field that constantly evolves with new techniques, algorithms, and technologies. Opting for a program ensures you receive up-to-date education and access to the latest tools and methodologies. You’ll be equipped to adapt to changing industry trends and remain competitive in the job market. 
• Networking opportunities: Data science programs often provide opportunities to connect with industry professionals, faculty members, and fellow students. Building a strong network can open doors to collaborations, mentorship, internships, and job placements, enhancing your career prospects and professional growth. 
• Transferable skills : Many skills developed in a data science program. Such as critical thinking, problem-solving, and data analysis, are transferable to other domains. Even if you decide to transition to a different field in the future. The skills you acquire through a data science program can still be valuable and applicable. 

Overall, opting for a data science program can provide. You with a solid foundation, relevant skills, and a competitive edge in the data-driven world we live in today 

So, if you are a student and want to pursue a PhD in Data Science, take it phd admission 2023 . Then check out the eligibility criteria and the aspects that might affect your chances of getting admitted. You can also take some advice from other students. Who have already taken up such courses as they could share their experiences with you.  

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PhD in Data Science – Your Guide to Choosing a Doctorate Degree Program

Created by aasif.faizal

Professional opportunities in data science are growing incredibly fast. That’s great news for students looking to pursue a career as a data scientist. But it also means that there are a lot more options out there to investigate and understand before developing the best educational path for you.

A PhD is the most advanced data science degree you can get, reflecting a depth of knowledge and technical expertise that will put you at the top of your field.

This means that PhD programs are the most time-intensive degree option out there, typically requiring that students complete dissertations involving rigorous research. This means that PhDs are not for everyone. Indeed, many who work in the world of big data hold master’s degrees rather than PhDs, which tend to involve the same coursework as PhD programs without a dissertation component. However, for the right candidate, a PhD program is the perfect choice to become a true expert on your area of focus.

If you’ve concluded that a data science PhD is the right path for you, this guide is intended to help you choose the best program to suit your needs. It will walk through some of the key considerations while picking graduate data science programs and some of the nuts and bolts (like course load and tuition costs) that are part of the data science PhD decision-making process.

Data Science PhD vs. Masters: Choosing the right option for you

If you’re considering pursuing a data science PhD, it’s worth knowing that such an advanced degree isn’t strictly necessary in order to get good work opportunities. Many who work in the field of big data only hold master’s degrees, which is the level of education expected to be a competitive candidate for data science positions.

So why pursue a data science PhD?

Simply put, a PhD in data science will leave you qualified to enter the big data industry at a high level from the outset.

You’ll be eligible for advanced positions within companies, holding greater responsibilities, keeping more direct communication with leadership, and having more influence on important data-driven decisions. You’re also likely to receive greater compensation to match your rank.

However, PhDs are not for everyone. Dissertations require a great deal of time and an interest in intensive research. If you are eager to jumpstart a career quickly, a master’s program will give you the preparation you need to hit the ground running. PhDs are appropriate for those who want to commit their time and effort to schooling as a long-term investment in their professional trajectory.

For more information on the difference between data science PhD’s and master’s programs, take a look at our guide here.

Topics include:

• Can I get an Online Ph.D in Data Science?
• Overview of Ph.d Coursework

Preparing for a Doctorate Program

Building a solid track record of professional experience, things to consider when choosing a school.

• What Does it Cost to Get a Ph.D in Data Science?
• School Listings

Data Science PhD Programs, Historically

Historically, data science PhD programs were one of the main avenues to get a good data-related position in academia or industry. But, PhD programs are heavily research oriented and require a somewhat long term investment of time, money, and energy to obtain. The issue that some data science PhD holders are reporting, especially in industry settings, is that that the state of the art is moving so quickly, and that the data science industry is evolving so rapidly, that an abundance of research oriented expertise is not always what’s heavily sought after.

Instead, many companies are looking for candidates who are up to date with the latest data science techniques and technologies, and are willing to pivot to match emerging trends and practices.

One recent development that is making the data science graduate school decisions more complex is the introduction of specialty master’s degrees, that focus on rigorous but compact, professional training. Both students and companies are realizing the value of an intensive, more industry-focused degree that can provide sufficient enough training to manage complex projects and that are more client oriented, opposed to research oriented.

However, not all prospective data science PhD students are looking for jobs in industry. There are some pretty amazing research opportunities opening up across a variety of academic fields that are making use of new data collection and analysis tools. Experts that understand how to leverage data systems including statistics and computer science to analyze trends and build models will be in high demand.

Can You Get a PhD in Data Science Online?

While it is not common to get a data science Ph.D. online, there are currently two options for those looking to take advantage of the flexibility of an online program.

Indiana University Bloomington and Northcentral University both offer online Ph.D. programs with either a minor or specialization in data science.

Given the trend for schools to continue increasing online offerings, expect to see additional schools adding this option in the near future.

Overview of PhD Coursework

A PhD requires a lot of academic work, which generally requires between four and five years (sometimes longer) to complete.

Here are some of the high level factors to consider and evaluate when comparing data science graduate programs.

How many credits are required for a PhD in data science?

On average, it takes 71 credits to graduate with a PhD in data science — far longer (almost double) than traditional master’s degree programs. In addition to coursework, most PhD students also have research and teaching responsibilities that can be simultaneously demanding and really great career preparation.

What’s the core curriculum like?

In a data science doctoral program, you’ll be expected to learn many skills and also how to apply them across domains and disciplines. Core curriculums will vary from program to program, but almost all will have a core foundation of statistics.

All PhD candidates will have to take a qualifying exam. This can vary from university to university, but to give you some insight, it is broken up into three phases at Yale. They have a practical exam, a theory exam and an oral exam. The goal is to make sure doctoral students are developing the appropriate level of expertise.

Dissertation

One of the final steps of a PhD program involves presenting original research findings in a formal document called a dissertation. These will provide background and context, as well as findings and analysis, and can contribute to the understanding and evolution of data science. A dissertation idea most often provides the framework for how a PhD candidate’s graduate school experience will unfold, so it’s important to be thoughtful and deliberate while considering research opportunities.

Since data science is such a rapidly evolving field and because choosing the right PhD program is such an important factor in developing a successful career path, there are some steps that prospective doctoral students can take in advance to find the best-fitting opportunity.

Join professional associations

Even before being fully credentials, joining professional associations and organizations such as the Data Science Association and the American Association of Big Data Professionals is a good way to get exposure to the field. Many professional societies are welcoming to new members and even encourage student participation with things like discounted membership fees and awards and contest categories for student researchers. One of the biggest advantages to joining is that these professional associations bring together other data scientists for conference events, research-sharing opportunities, networking and continuing education opportunities.

Leverage your social network

Be on the lookout to make professional connections with professors, peers, and members of industry. There are a number of LinkedIn groups dedicated to data science. A well-maintained professional network is always useful to have when looking for advice or letters of recommendation while applying to graduate school and then later while applying for jobs and other career-related opportunities.

Kaggle competitions

Kaggle competitions provide the opportunity to solve real-world data science problems and win prizes. A list of data science problems can be found at Kaggle.com . Winning one of these competitions is a good way to demonstrate professional interest and experience.

Internships

Internships are a great way to get real-world experience in data science while also getting to work for top names in the world of business. For example, IBM offers a data science internship which would also help to stand out when applying for PhD programs, as well as in seeking employment in the future.

Demonstrating professional experience is not only important when looking for jobs, but it can also help while applying for graduate school. There are a number of ways for prospective students to gain exposure to the field and explore different facets of data science careers.

Get certified

There are a number of data-related certificate programs that are open to people with a variety of academic and professional experience. DeZyre has an excellent guide to different certifications, some of which might help provide good background for graduate school applications.

Conferences

Conferences are a great place to meet people presenting new and exciting research in the data science field and bounce ideas off of newfound connections. Like professional societies and organizations, discounted student rates are available to encourage student participation. In addition, some conferences will waive fees if you are presenting a poster or research at the conference, which is an extra incentive to present.

It can be hard to quantify what makes a good-fit when it comes to data science graduate school programs. There are easy to evaluate factors, such as cost and location, and then there are harder to evaluate criteria such as networking opportunities, accessibility to professors, and the up-to-dateness of the program’s curriculum.

Nevertheless, there are some key relevant considerations when applying to almost any data science graduate program.

What most schools will require when applying:

• All undergraduate and graduate transcripts
• A statement of intent for the program (reason for applying and future plans)
• Letters of reference
• Application fee
• Online application
• A curriculum vitae (outlining all of your academic and professional accomplishments)

What Does it Cost to Get a PhD in Data Science?

The great news is that many PhD data science programs are supported by fellowships and stipends. Some are completely funded, meaning the school will pay tuition and basic living expenses. Here are several examples of fully funded programs:

• University of Southern California
• University of Nevada, Reno
• Kennesaw State University
• Worcester Polytechnic Institute
• University of Maryland

For all other programs, the average range of tuition, depending on the school can range anywhere from $1,300 per credit hour to $2,000 amount per credit hour. Remember, typical PhD programs in data science are between 60 and 75 credit hours, meaning you could spend up to $150,000 over several years.

That’s why the financial aspects are so important to evaluate when assessing PhD programs, because some schools offer full stipends so that you are able to attend without having to find supplemental scholarships or tuition assistance.

Can I become a professor of data science with a PhD.? Yes! If you are interested in teaching at the college or graduate level, a PhD is the degree needed to establish the full expertise expected to be a professor. Some data scientists who hold PhDs start by entering the field of big data and pivot over to teaching after gaining a significant amount of work experience. If you’re driven to teach others or to pursue advanced research in data science, a PhD is the right degree for you.

Do I need a master’s in order to pursue a PhD.? No. Many who pursue PhDs in Data Science do not already hold advanced degrees, and many PhD programs include all the coursework of a master’s program in the first two years of school. For many students, this is the most time-effective option, allowing you to complete your education in a single pass rather than interrupting your studies after your master’s program.

Can I choose to pursue a PhD after already receiving my master’s? Yes. A master’s program can be an opportunity to get the lay of the land and determine the specific career path you’d like to forge in the world of big data. Some schools may allow you to simply extend your academic timeline after receiving your master’s degree, and it is also possible to return to school to receive a PhD if you have been working in the field for some time.

If a PhD. isn’t necessary, is it a waste of time? While not all students are candidates for PhDs, for the right students – who are keen on doing in-depth research, have the time to devote to many years of school, and potentially have an interest in continuing to work in academia – a PhD is a great choice. For more information on this question, take a look at our article Is a Data Science PhD. Worth It?

Complete List of Data Science PhD Programs

Below you will find the most comprehensive list of schools offering a doctorate in data science. Each school listing contains a link to the program specific page, GRE or a master’s degree requirements, and a link to a page with detailed course information.

Note that the listing only contains true data science programs. Other similar programs are often lumped together on other sites, but we have chosen to list programs such as data analytics and business intelligence on a separate section of the website.

Boise State University  – Boise, Idaho PhD in Computing – Data Science Concentration

The Data Science emphasis focuses on the development of mathematical and statistical algorithms, software, and computing systems to extract knowledge or insights from data.  

In 60 credits, students complete an Introduction to Graduate Studies, 12 credits of core courses, 6 credits of data science elective courses, 10 credits of other elective courses, a Doctoral Comprehensive Examination worth 1 credit, and a 30-credit dissertation.

Electives can be taken in focus areas such as Anthropology, Biometry, Ecology/Evolution and Behavior, Econometrics, Electrical Engineering, Earth Dynamics and Informatics, Geoscience, Geostatistics, Hydrology and Hydrogeology, Materials Science, and Transportation Science.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $7,236 total (Resident), $24,573 total (Non-resident)

View Course Offerings

Bowling Green State University  – Bowling Green, Ohio Ph.D. in Data Science

Data Science students at Bowling Green intertwine knowledge of computer science with statistics.

Students learn techniques in analyzing structured, unstructured, and dynamic datasets.

Courses train students to understand the principles of analytic methods and articulating the strengths and limitations of analytical methods.

The program requires 60 credit hours in the studies of Computer Science (6 credit hours), Statistics (6 credit hours), Data Science Exploration and Communication, Ethical Issues, Advanced Data Mining, and Applied Data Science Experience.

Students must also complete 21 credit hours of elective courses, a qualifying exam, a preliminary exam, and a dissertation.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $8,418 (Resident), $14,410 (Non-resident)

Brown University  – Providence, Rhode Island PhD in Computer Science – Concentration in Data Science

Brown University’s database group is a world leader in systems-oriented database research; they seek PhD candidates with strong system-building skills who are interested in researching TupleWare, MLbase, MDCC, Crowd DB, or PIQL.

In order to gain entrance, applicants should consider first doing a research internship at Brown with this group. Other ways to boost an application are to take and do well at massive open online courses, do an internship at a large company, and get involved in a large open-source software project.

Coding well in C++ is preferred.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $62,680 total

Chapman University  – Irvine, California Doctorate in Computational and Data Sciences

Candidates for the doctorate in computational and data science at Chapman University begin by completing 13 core credits in basic methodologies and techniques of computational science.

Students complete 45 credits of electives, which are personalized to match the specific interests and research topics of the student.

Finally, students complete up to 12 credits in dissertation research.

Applicants must have completed courses in differential equations, data structures, and probability and statistics, or take specific foundation courses, before beginning coursework toward the PhD.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $37,538 per year

Clemson University / Medical University of South Carolina (MUSC) – Joint Program – Clemson, South Carolina & Charleston, South Carolina Doctor of Philosophy in Biomedical Data Science and Informatics – Clemson

The PhD in biomedical data science and informatics is a joint program co-authored by Clemson University and the Medical University of South Carolina (MUSC).

Students choose one of three tracks to pursue: precision medicine, population health, and clinical and translational informatics. Students complete 65-68 credit hours, and take courses in each of 5 areas: biomedical informatics foundations and applications; computing/math/statistics/engineering; population health, health systems, and policy; biomedical/medical domain; and lab rotations, seminars, and doctoral research.

Applicants must have a bachelor’s in health science, computing, mathematics, statistics, engineering, or a related field, and it is recommended to also have competency in a second of these areas.

Program requirements include a year of calculus and college biology, as well as experience in computer programming.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $10,858 total (South Carolina Resident), $22,566 total (Non-resident)

View Course Offerings – Clemson

George Mason University  – Fairfax, Virginia Doctor of Philosophy in Computational Sciences and Informatics – Emphasis in Data Science

George Mason’s PhD in computational sciences and informatics requires a minimum of 72 credit hours, though this can be reduced if a student has already completed a master’s. 48 credits are toward graduate coursework, and an additional 24 are for dissertation research.

Students choose an area of emphasis—either computer modeling and simulation or data science—and completed 18 credits of the coursework in this area. Students are expected to completed the coursework in 4-5 years.

Applicants to this program must have a bachelor’s degree in a natural science, mathematics, engineering, or computer science, and must have knowledge and experience with differential equations and computer programming.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $13,426 total (Virginia Resident), $35,377 total (Non-resident)

Harrisburg University of Science and Technology  – Harrisburg, Pennsylvania Doctor of Philosophy in Data Sciences

Harrisburg University’s PhD in data science is a 4-5 year program, the first 2 of which make up the Harrisburg master’s in analytics.

Beyond this, PhD candidates complete six milestones to obtain the degree, including 18 semester hours in doctoral-level courses, such as multivariate data analysis, graph theory, machine learning.

Following the completion of ANLY 760 Doctoral Research Seminar, students in the program complete their 12 hours of dissertation research bringing the total program hours to 36.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $14,940 total

Icahn School of Medicine at Mount Sinai  – New York, New York Genetics and Data Science, PhD

As part of the Biomedical Science PhD program, the Genetics and Data Science multidisciplinary training offers research opportunities that expand on genetic research and modern genomics. The training also integrates several disciplines of biomedical sciences with machine learning, network modeling, and big data analysis.

Students in the Genetics and Data Science program complete a predetermined course schedule with a total of 64 credits and 3 years of study.

Additional course requirements and electives include laboratory rotations, a thesis proposal exam and thesis defense, Computer Systems, Intro to Algorithms, Machine Learning for Biomedical Data Science, Translational Genomics, and Practical Analysis of a Personal Genome.

Delivery Method: Campus GRE: Not Required 2022-2023 Tuition: $31,303 total

Indiana University-Purdue University Indianapolis  – Indianapolis, Indiana PhD in Data Science PhD Minor in Applied Data Science

Doctoral candidates pursuing the PhD in data science at Indiana University-Purdue must display competency in research, data analytics, and at management and infrastructure to earn the degree.

The PhD is comprised of 24 credits of a data science core, 18 credits of methods courses, 18 credits of a specialization, written and oral qualifying exams, and 30 credits of dissertation research. All requirements must be completed within 7 years.

Applicants are generally expected to have a master’s in social science, health, data science, or computer science. 

Currently a majority of the PhD students at IUPUI are funded by faculty grants and two are funded by the federal government. None of the students are self funded.

IUPUI also offers a PhD Minor in Applied Data Science that is 12-18 credits. The minor is open to students enrolled at IUPUI or IU Bloomington in a doctoral program other than Data Science.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $9,228 per year (Indiana Resident), $25,368 per year (Non-resident)

Jackson State University – Jackson, Mississippi PhD Computational and Data-Enabled Science and Engineering

Jackson State University offers a PhD in computational and data-enabled science and engineering with 5 concentration areas: computational biology and bioinformatics, computational science and engineering, computational physical science, computation public health, and computational mathematics and social science.

Students complete 12 credits of common core courses, 12 credits in the specialization, 24 credits of electives, and 24 credits in dissertation research.

Students may complete the doctoral program in as little as 5 years and no more than 8 years.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $8,270 total

Kennesaw State University  – Kennesaw, Georgia PhD in Analytics and Data Science

Students pursuing a PhD in analytics and data science at Kennesaw State University must complete 78 credit hours: 48 course hours and 6 electives (spread over 4 years of study), a minimum 12 credit hours for dissertation research, and a minimum 12 credit-hour internship.

Prior to dissertation research, the comprehensive examination will cover material from the three areas of study: computer science, mathematics, and statistics.

Successful applicants will have a master’s degree in a computational field, calculus I and II, programming experience, modeling experience, and are encouraged to have a base SAS certification.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $5,328 total (Georgia Resident), $19,188 total (Non-resident)

New Jersey Institute of Technology  – Newark, New Jersey PhD in Business Data Science

Students may enter the PhD program in business data science at the New Jersey Institute of Technology with either a relevant bachelor’s or master’s degree. Students with bachelor’s degrees begin with 36 credits of advanced courses, and those with master’s take 18 credits before moving on to credits in dissertation research.

Core courses include business research methods, data mining and analysis, data management system design, statistical computing with SAS and R, and regression analysis.

Students take qualifying examinations at the end of years 1 and 2, and must defend their dissertations successfully by the end of year 6.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $21,932 total (New Jersey Resident), $32,426 total (Non-resident)

New York University  – New York, New York PhD in Data Science

Doctoral candidates in data science at New York University must complete 72 credit hours, pass a comprehensive and qualifying exam, and defend a dissertation with 10 years of entering the program.

Required courses include an introduction to data science, probability and statistics for data science, machine learning and computational statistics, big data, and inference and representation.

Applicants must have an undergraduate or master’s degree in fields such as mathematics, statistics, computer science, engineering, or other scientific disciplines. Experience with calculus, probability, statistics, and computer programming is also required.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $37,332 per year

View Course Offering

Northcentral University  – San Diego, California PhD in Data Science-TIM

Northcentral University offers a PhD in technology and innovation management with a specialization in data science.

The program requires 60 credit hours, including 6-7 core courses, 3 in research, a PhD portfolio, and 4 dissertation courses.

The data science specialization requires 6 courses: data mining, knowledge management, quantitative methods for data analytics and business intelligence, data visualization, predicting the future, and big data integration.

Applicants must have a master’s already.

Delivery Method: Online GRE: Required 2022-2023 Tuition: $16,794 total

Stevens Institute of Technology – Hoboken, New Jersey Ph.D. in Data Science

Stevens Institute of Technology has developed a data science Ph.D. program geared to help graduates become innovators in the space.

The rigorous curriculum emphasizes mathematical and statistical modeling, machine learning, computational systems and data management.

The program is directed by Dr. Ted Stohr, a recognized thought leader in the information systems, operations and business process management arenas.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $39,408 per year

University at Buffalo – Buffalo, New York PhD Computational and Data-Enabled Science and Engineering

The curriculum for the University of Buffalo’s PhD in computational and data-enabled science and engineering centers around three areas: data science, applied mathematics and numerical methods, and high performance and data intensive computing. 9 credit course of courses must be completed in each of these three areas. Altogether, the program consists of 72 credit hours, and should be completed in 4-5 years. A master’s degree is required for admission; courses taken during the master’s may be able to count toward some of the core coursework requirements.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $11,310 per year (New York Resident), $23,100 per year (Non-resident)

University of Colorado Denver – Denver, Colorado PhD in Big Data Science and Engineering

The University of Colorado – Denver offers a unique program for those students who have already received admission to the computer science and information systems PhD program.

The Big Data Science and Engineering (BDSE) program is a PhD fellowship program that allows selected students to pursue research in the area of big data science and engineering. This new fellowship program was created to train more computer scientists in data science application fields such as health informatics, geosciences, precision and personalized medicine, business analytics, and smart cities and cybersecurity.

Students in the doctoral program must complete 30 credit hours of computer science classes beyond a master’s level, and 30 credit hours of dissertation research.

The BDSE fellowship requires students to have an advisor both in the core disciplines (either computer science or mathematics and statistics) as well as an advisor in the application discipline (medicine and public health, business, or geosciences).

In addition, the fellowship covers full stipend, tuition, and fees up to ~50k for BDSE fellows annually. Important eligibility requirements can be found here.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $55,260 total

University of Marylan d  – College Park, Maryland PhD in Information Studies

Data science is a potential research area for doctoral candidates in information studies at the University of Maryland – College Park. This includes big data, data analytics, and data mining.

Applicants for the PhD must have taken the following courses in undergraduate studies: programming languages, data structures, design and analysis of computer algorithms, calculus I and II, and linear algebra.

Students must complete 6 qualifying courses, 2 elective graduate courses, and at least 12 credit hours of dissertation research.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $16,238 total (Maryland Resident), $35,388 total (Non-resident)

University of Massachusetts Boston  – Boston, Massachusetts PhD in Business Administration – Information Systems for Data Science Track

The University of Massachusetts – Boston offers a PhD in information systems for data science. As this is a business degree, students must complete coursework in their first two years with a focus on data for business; for example, taking courses such as business in context: markets, technologies, and societies.

Students must take and pass qualifying exams at the end of year 1, comprehensive exams at the end of year 2, and defend their theses at the end of year 4.

Those with a degree in statistics, economics, math, computer science, management sciences, information systems, and other related fields are especially encouraged, though a quantitative degree is not necessary.

Students accepted by the program are ordinarily offered full tuition credits and a stipend ($25,000 per year) to cover educational expenses and help defray living costs for up to three years of study.

During the first two years of coursework, they are assigned to a faculty member as a research assistant; for the third year students will be engaged in instructional activities. Funding for the fourth year is merit-based from a limited pool of program funds

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $18,894 total (in-state), $36,879 (out-of-state)

University of Nevada Reno – Reno, Nevada PhD in Statistics and Data Science

The University of Nevada – Reno’s doctoral program in statistics and data science is comprised of 72 credit hours to be completed over the course of 4-5 years. Coursework is all within the scope of statistics, with titles such as statistical theory, probability theory, linear models, multivariate analysis, statistical learning, statistical computing, time series analysis.

The completion of a Master’s degree in mathematics or statistics prior to enrollment in the doctoral program is strongly recommended, but not required.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $5,814 total (in-state), $22,356 (out-of-state)

University of Southern California – Los Angles, California PhD in Data Sciences & Operations

USC Marshall School of Business offers a PhD in data sciences and operations to be completed in 5 years.

Students can choose either a track in operations management or in statistics. Both tracks require 4 courses in fall and spring of the first 2 years, as well as a research paper and courses during the summers. Year 3 is devoted to dissertation preparation and year 4 and/or 5 to dissertation defense.

A bachelor’s degree is necessary for application, but no field or further experience is required.

Students should complete 60 units of coursework. If the students are admitted with Advanced Standing (e.g., Master’s Degree in appropriate field), this requirement may be reduced to 40 credits.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $63,468 total

University of Tennessee-Knoxville  – Knoxville, Tennessee The Data Science and Engineering PhD

The data science and engineering PhD at the University of Tennessee – Knoxville requires 36 hours of coursework and 36 hours of dissertation research. For those entering with an MS degree, only 24 hours of course work is required.

The core curriculum includes work in statistics, machine learning, and scripting languages and is enhanced by 6 hours in courses that focus either on policy issues related to data, or technology entrepreneurship.

Students must also choose a knowledge specialization in one of these fields: health and biological sciences, advanced manufacturing, materials science, environmental and climate science, transportation science, national security, urban systems science, and advanced data science.

Applicants must have a bachelor’s or master’s degree in engineering or a scientific field. 

All students that are admitted will be supported by a research fellowship and tuition will be included.

Many students will perform research with scientists from Oak Ridge national lab, which is located about 30 minutes drive from campus.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $11,468 total (Tennessee Resident), $29,656 total (Non-resident)

University of Vermont – Burlington, Vermont Complex Systems and Data Science (CSDS), PhD

Through the College of Engineering and Mathematical Sciences, the Complex Systems and Data Science (CSDS) PhD program is pan-disciplinary and provides computational and theoretical training. Students may customize the program depending on their chosen area of focus.

Students in this program work in research groups across campus.

Core courses include Data Science, Principles of Complex Systems and Modeling Complex Systems. Elective courses include Machine Learning, Complex Networks, Evolutionary Computation, Human/Computer Interaction, and Data Mining.

The program requires at least 75 credits to graduate with approval by the student graduate studies committee.

Delivery Method: Campus GRE: Not Required 2022-2023 Tuition: $12,204 total (Vermont Resident), $30,960 total (Non-resident)

University of Washington Seattle Campus – Seattle, Washington PhD in Big Data and Data Science

The University of Washington’s PhD program in data science has 2 key goals: training of new data scientists and cyberinfrastructure development, i.e., development of open-source tools and services that scientists around the world can use for big data analysis.

Students must take core courses in data management, machine learning, data visualization, and statistics.

Students are also required to complete at least one internship that covers practical work in big data.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $17,004 per year (Washington resident), $30,477 (non-resident)

University of Wisconsin-Madison – Madison, Wisconsin PhD in Biomedical Data Science

The PhD program in Biomedical Data Science offered by the Department of Biostatistics and Medical Informatics at UW-Madison is unique, in blending the best of statistics and computer science, biostatistics and biomedical informatics. 

Students complete three year-long course sequences in biostatistics theory and methods, computer science/informatics, and a specialized sequence to fit their interests.

Students also complete three research rotations within their first two years in the program, to both expand their breadth of knowledge and assist in identifying a research advisor.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $10,728 total (in-state), $24,054 total (out-of-state)

Vanderbilt University – Nashville, Tennessee Data Science Track of the BMI PhD Program

The PhD in biomedical informatics at Vanderbilt has the option of a data science track.

Students complete courses in the areas of biomedical informatics (3 courses), computer science (4 courses), statistical methods (4 courses), and biomedical science (2 courses). Students are expected to complete core courses and defend their dissertations within 5 years of beginning the program.

Applicants must have a bachelor’s degree in computer science, engineering, biology, biochemistry, nursing, mathematics, statistics, physics, information management, or some other health-related field.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $53,160 per year

Washington University in St. Louis – St. Louis, Missouri Doctorate in Computational & Data Sciences

Washington University now offers an interdisciplinary Ph.D. in Computational & Data Sciences where students can choose from one of four tracks (Computational Methodologies, Political Science, Psychological & Brain Sciences, or Social Work & Public Health).

Students are fully funded and will receive a stipend for at least five years contingent on making sufficient progress in the program.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $59,420 total

Worcester Polytechnic Institute – Worcester, Massachusetts PhD in Data Science

The PhD in data science at Worcester Polytechnic Institute focuses on 5 areas: integrative data science, business intelligence and case studies, data access and management, data analytics and mining, and mathematical analysis.

Students first complete a master’s in data science, and then complete 60 credit hours beyond the master’s, including 30 credit hours of research.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $28,980 per year

Yale University – New Haven, Connecticut PhD Program – Department of Stats and Data Science

The PhD in statistics and data science at Yale University offers broad training in the areas of statistical theory, probability theory, stochastic processes, asymptotics, information theory, machine learning, data analysis, statistical computing, and graphical methods. Students complete 12 courses in the first year in these topics.

Students are required to teach one course each semester of their third and fourth years.

Most students complete and defend their dissertations in their fifth year.

Applicants should have an educational background in statistics, with an undergraduate major in statistics, mathematics, computer science, or similar field.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $46,900 total

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• Finding inspiration at the intersection of public health and data science

Soumik Purkayastha, MS ’21, PhD ’24

• Biostatistics

April 15, 2024

A native of India, Soumik Purkayastha, MS ’21, PhD ’24, first made a connection with the University of Michigan School of Public Health in 2005.

Purkayastha was born in Chandannagar, a town about the same size and population as Ann Arbor, in the state of West Bengal. He spent most of his childhood with his parents in Kolkata or with his grandparents in Chandannagar. 

A visit to Ann Arbor when he was in fourth grade would leave an indelible impression on Purkayastha and set him on a path toward a career in public health.

“My father visited the Department of Biostatistics during his sabbatical year,” he said. “My mother and I were able to join him for a few months here in Ann Arbor. Later, when I was applying to graduate programs in the United States, the program here was very attractive because not only was it a great program, but I felt a personal connection to the school and the town at large.

It’s encouraging to see how the integration of data science in public health contributes to improved health outcomes. In many ways, I feel our work is meaningful and well-received not just in clinical circles but also by policymakers and the media.”

“Back in 2005, I had no way of knowing I’d be spending a good chunk of my 20s in Ann Arbor, but now I can look back and connect some dots.”

For Purkayastha, one of the most interesting things about public health is how he keeps learning about exciting ways in which public health and data science intersect.

“It’s encouraging to see how the integration of data science in public health contributes to improved health outcomes,” he said. “In many ways, I feel our work is meaningful and well-received not just in clinical circles but also by policymakers and the media.”

During the COVID-19 pandemic, Purkayastha had an opportunity to work on spatio-temporal forecasting of infectious diseases. His areas of focus included infection rates in India, comparing and understanding how different transmission models work, as well as developing a transmission data-driven framework to help inform public health policy.

“What I enjoyed the most was getting to learn from epidemiologists, biostatistics, economists and policy experts at a time when we were all confined to our apartments,” Purkayastha said. “It was a time when all of us struggled, yet our collective efforts at understanding what was going on in the world around us gave me a sense of purpose—and I cherish that.

“I think working in public health gives me a sense of direction on what to do with my skill set while also finding meaning in the work I do.”

Purkayastha will graduate in May with a PhD in Biostatistics from the Department of Biostatistics at Michigan Public Health. He earned a Master of Science in Biostatistics from Michigan Public Health after receiving bachelor’s and master’s degrees in Statistics from St. Xavier’s College and the Indian Statistical Institute respectively, both of Kolkata, India.

Driving change with biostatistics

He found meaning in working with the student organization STATCOM: Statistics in the Community .

“I’m proud to say that my department is home to STATCOM, a community outreach program provided by graduate students at the University of Michigan,” Purkayastha said.

The program offers the expertise of graduate students—free of charge—to nonprofit governmental and community organizations in the areas of data organization, analysis, and interpretation.

“I have been very fortunate to find meaningful consulting work with a host of community partners,” he said. “From 2022-23, I had the honor of serving as co-president of STATCOM. It has been both challenging as well as rewarding. I expect to continue with STATCOM until I graduate.”

A few of STATCOM’s recent projects include partnerships with:

• The Michigan Center for Youth Justice (MCYJ): STATCOM’s partnership with the MCYJ revolves around understanding the patterns of special investigations and violations occurring in juvenile justice facilities throughout the state.
• The Detroit Housing Commission (DHC) and Poverty Solutions (PS): STATCOM has been working with the DHC and PS to investigate evictions among families with children in Detroit to reduce accompanied and unaccompanied youth homelessness rates.
• Stand with Trans (SWT): STATCOM is collaborating with SWT to identify gaps in—and further improve—online resources that are designed to empower and support transgender youth.

Purkayastha also worked as a research assistant at the University of Michigan, studying diabetes.

“I worked with doctors and clinical experts to study diabetic foot ulcers,” he said. “They’re a major cause of amputation in US adults. With diabetes prevalence rising, understanding how these ulcers behave is crucial not only from a surgical perspective but also from a preventive viewpoint. It was a wonderful experience getting to apply my technical skills to real diabetes data to derive insights through statistics and visualization tools. I learned a lot about the disease from medical professionals as well.

“I think the work biostatisticians do is helpful for practitioners and policymakers as we learn more about disease prediction and prevention. Most importantly, the work we do in public health must be accessible and informative to the public. I think it’s incredibly important that we use all our skills to advocate for public health initiatives, policies and practices.”

In addition, Purkayastha had an internship with Apple in California, where he learned about language models.

“The future of language models in medicine, and public health is incredibly exciting,” he said. “I was also fortunate to receive the Rackham Predoctoral Fellowship for my final dissertation year. It allowed me to focus on developing new research projects and spend a lot of time thinking about cool, new ideas.”

Working in public health is ‘incredibly rewarding’

After graduation, Purkayastha will join the Department of Biostatistics at the University of Pittsburgh as an assistant professor in the fall. He will be engaged in methodological and applied public health research in addition to teaching and mentoring younger students in public health education and research.

“Soumik is a terrific example of the best of Michigan graduates; His dedication to translational biostatistics is inspiring,” said Bhramar Mukherjee , the John D. Kalbfleisch Distinguished University Professor of Biostatistics and Siobán D. Harlow Collegiate Professor of Public Health. “His work is grounded in solid theory and computation but has profound public health impact. He has been an amazing student leader through his work in departmental committees and through our flagship student organization STATCOM. I look forward to his scholarly career after graduation. I know he will make a difference.” 

I think the work biostatisticians do is helpful for practitioners and policymakers as we learn more about disease prediction and prevention. Most importantly, the work we do in public health must be accessible and informative to the public. I think it’s incredibly important that we use all our skills to advocate for public health initiatives, policies and practices.”

Purkayastha said he thrives on the satisfaction of knowing that his efforts in public health are making a positive impact on the health and well-being of individuals and communities.

“I feel it can be incredibly rewarding on a personal level for many others as well,” he said. “I have seen firsthand how the work we do translates to changes in governance and policy making. Further, there is an increasing need for health data scientists, who use their data skills for the public good. And it’s not just biostatistics, public health offers a wide range of career paths and specialties, including epidemiology, health education, policy development, environmental health and global health. This diversity allows individuals to find roles that align with someone’s interests, skills and passions, creating opportunities for personal and professional growth.

“I’m satisfied with my career choices so far. Working in public health allows me to focus on a lot of things I’m interested in while building something useful for communities at large. It’s a good feeling, and I wish that for everyone.”

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Data Science Ph.D.

A dynamic data science environment.

Graduates of our program—the first of its kind in both Indiana and the Big Ten—develop the skills to make pioneering research contributions to data science theory and practice in academic and the industrial sectors.

Our students acquire the skills to develop inventive and creative solutions to data research problems—solutions that demonstrate a high degree of intellectual merit and the potential for broader impact. The Ph.D. curriculum also prepares students to make research contributions that advance the theory and practice of data science.

A leader in data science research

The Data Science Ph.D. Program at IU Indianapolis provides a world-class education and research opportunities. Ph.D. students in the program learn fundamental Data Science methods while pursuing independent, original research in a broad variety of topics, including:

• Novel techniques for Natural Language Processing and Text Analytics.
• Applications of AI to social welfare, digital governance, cultural heritage, biomedical sciences, and environmental sustainability.
• Intelligent conversational agents and models of Human-AI collaboration.
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Meet our faculty

The program is in the midst of a major expansion, with over 50 graduate students joining the program in the past year alone. Multiple faculty in our department have secured high-profile research grants, including three    active   CAREER awards, the National Science Foundation’s most prestigious award for early-career faculty. The IU Indianapolis campus hosts the newly created Institute of Integrative Artificial Intelligence, providing an interdisciplinary nexus between Data Science, AI, and various science and engineering fields.

Sunandan Chakraborty

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Leon Johnson

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Kyle M. L. Jones

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