data science phd paris

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Data Science Program

The production and collection of massive amounts of data, combined with advances in storage, analysis and processing capacities, opened up unprecedented scientific perspectives in many disciplines, such as life sciences, cognitive sciences, astrophysics and quantitative sociology. The Data Science cross-disciplinary program covers the PSL education in AI and at the interfaces of other scientific disciplines. Thanks to the scientific richness of PSL in AI and other scientific disciplines and its involvement in the PRAIRIE institute , the Data Science cross-disciplinary Program offers a training of excellence in AI for students with any background.

[New in 2023] 

• To enable all master's and PhD students at PSL University to learn about or specialize in AI and data science, whatever their field of expertise, the DATA program is launching a brand-new certifying minor from the start of the 2023 academic year.
• The DATA program at Université PSL also offers training for academics in data science and artificial intelligence to all PSL researchers, PhD students and postdoc, adapted to their disciplines and levels (beginners, advanced, expert).

For students majoring in other subjects

If you are following a master's degree in another subject than mathematics and computer science, and if you want to include AI in your curriculum, the university-wide Data Science program includes a two-step training:

• Two-week intensive preparation in order to learn the basics of AI and to equip you with enough background to follow several MASH and IASD Masters' courses
• Intensive weeks on AI at the interfaces

Two preparatory weeks are offered. These are precontions for the certificate (unless the student demonstrates comparable skills as part of a previous course of study).

•  Week 1 – Fundamentals of Mathematics and Computer Science (3 ECTS) | The basics of mathematics and computer science for data science. The week can be followed asynchronously.
• Week 2 - Machine Learning and Database (3 ECTS) | This takes place at the end of August/beginning of September on the PariSanté Campus.

The 2024 program for these 2 weeks will be published soon.

Intensive DATA weeks are PSL weeks providing scientific and technical immersion in AI, at the interface with another discipline. 2 ECTS are awarded at the end of each week.

Details of the program can be found on the PSL weeks website .

PSL weeks from 27 November 2023 to 1st December 2024:

• AI for Economics and Finance
• Explainability and Interpretability in Artificial Neural Networks
• Ethique et Intelligence Artificielle
• NLP for Social Sciences
• Neuro and Bio-robotics: senses and perception

PSL weeks from 4 March 2024 to 8 March 2024:

• Digital Humanities meet Artificial Intelligence
• Machine learning for physics and engineering
• Green Artificial Intelligence
• Machine learning in Genomics
• Statistical Physics and Machine Learning
• Data mining and modeling for behavioral sciences and beyond

COFUND: Artificial Intelligence for the Sciences (AI4theSciences)

Artificial Intelligence for the Sciences (AI4theSciences) is a doctoral program run by Université PSL. 26 Ph.D. contracts at the interfaces of artificial intelligence or big data processing are offered. AI4theSciences is supported and jointly funded by the Horizon 2020-Marie Skłodowska-Curie Actions-COFUND European program.

This unique and structured project invites an international audience. It aims to create a research community from multiple PSL laboratories and schools, along with a dozen private and public partners. AI4theSciences is one of the PSL initiatives that contribute to strengthening PSL research on a key challenge of our century. It benefits from a particularly useful and evolving environment for the doctoral students in the program and, more broadly, for the PSL research community.

All disciplines are eligible for co-funding (physics, chemistry, history, economics, etc.) as long as the doctoral dissertation includes artificial intelligence or big data processing techniques. In addition to the training courses specific to each doctoral grant, a program of training courses and specific events will be created: first courses on AI/big data, seminars, conferences, etc. Each doctoral student will benefit from dual supervision composed of a PSL dissertation adviser specialized in their discipline and a co-adviser specialized in artificial intelligence or big data techniques (possibly from an independent laboratory outside or a private partner).

Initiated in 2020, AI4theSciences is planned to run for six years.

Alexandre Allauzen (ESPCI Paris - PSL)

[email protected]

(For PSL students)

More information

Data science & AI for academics

(For PSL researchers, Phd students & postdoc)

MSc Courses on Data Science and Artificial Intelligence

The diiP institute initiated the creation of the Graduate School of Artificial Intelligence and Data Science (grAIds) , which aims to train Master’s students on the most advanced techniques in artificial intelligence (AI) and data science, with an emphasis on interdisciplinarity.

The Université Paris Cité represents a pool of exceptional talent in a very wide range of disciplines where the need for data analysis is high, and is already running several relevant Master’s-level programs. The Graduate School on Artificial Intelligence and Data Science (grAIds) gathers under the same roof all educational efforts related to methods in the intersection of AI, ML, statistical learning, data analytics, data science, data intelligence, which address fundamental data analysis challenges across disciplines. Moreover, grAIds offers several opportunities for interdisciplinary educational offerings and research initiatives, ranging from ranging from fundamental research in Artificial Intelligence and Data Science to the application of these techniques to various fields, including medicine and biology, chemistry and industry, engineering and integrated health monitoring, astrophysics and Earth sciences, and others. The grAIds graduate school runs in coordination with the actions of the Data Intelligence Institute of Paris (diiP), therefore better preparing our graduates for an interdisciplinary world. The list of associated Master’s programs, laboratories and doctoral schools can be found on the  grAIds webpage .

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2024 internship opportunities for Master’s students

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• Master and PhD track in computer science and AI
• Doctoral school in CS and AI
• Research Overview
• Publications
• Theme 1: CS in biotechnologies and health
• Theme 2: trust, safety and cybersecurity
• Theme 3: next generation digital infrastructures
• Theme 4: robotics, audio & visual computing, interaction
• Theme 5: foundations of CS
• Theme 6: data science and AI
• CSDAI environment
• LTCI – Information Processing and Communications Laboratory
• LIX – Computer Science Laboratory
• SAMOVAR laboratory
• U2IS – Computer Science and Systems Engineering Laboratory
• CMAP – Applied Mathematics Center
• INRIA Paris Saclay
• CIEDS center
• Hi!PARIS center

Computer science, data and artificial intelligence (CSDAI) is one of ten  disciplinary departments  at  Institut Polytechnique de Paris  bringing together top researchers and PhD students at state-of the art laboratories and infrastructures.

The CSDAI department has 211 permanent members (from IP Paris engineering schools, CNRS and INRIA) and around 300 PhD students (including 90 working with companies in the context of ANRT-CIFRE). It is one of the best computer science department in Europe (according to QS 2022, ranked #9 in Europe and first in France for the computer science and information systems subject).

Its members belongs to several research laboratories, LIX, LTCI, Samovar, U2IS and CMAP. The CSDAI department also contributes to interdisciplinary centers of IP Paris,  CIEDS ,  E4C , and  Hi!PARIS .

Its mission is to coordinate research and master, PhD track and PhD programs in computer science, data and artificial intelligence.

The CSDAI department of IP Paris is in charge of coordinating all teaching activities in computer science, data and artificial intelligence. Its first constructions are the master and PhD tracks in computer science .

The goal of this program is to teach students the theoretical foundations and the various concepts and tools of computer science. The program offers a vast coverage of different areas, including systems, networks, artificial intelligence, and cybersecurity, as well as algorithms and human-computer interaction. The program has a focus on research, and aims to integrate students into research labs through projects and during the master’s thesis, in order to prepare them for a PhD

The development of information technology has profoundly changed our society and given rise to new disciplines such as the processing of big, heterogeneous data and artificial intelligence to help produce new knowledge. In our digital society, research has never been so crucial in order to develop new methods and algorithms with wide-ranging impacts – whether on industry, the economy, sustainable development, or in other disciplinary areas where these new tools are needed to more fully analyze the data produced by their experiments and simulations.

Fundamental and applied research in computer science, data and artificial intelligence at the Institut Polytechnique de Paris aims to:

• Contribute to the foundations of computer science with a particular focus on interactions with mathematics,
• Develop powerful systems and algorithms to provide the basis for an efficient, reliable and secure digital world,
• Develop algorithms and statistical processing methods for learning, optimization and data analysis,
• Explore and roll out new AI applications for industry and society.

The main research topics of the CSDAI department are:

• Fundamentals of computer science, semantic, algorithmic verification, Combinatorics, computer algebra
• Data science, machine learning, artificial intelligence
• Digital trust, cybersecurity
• Robotics, Computer graphics; audio and video computing; virtual and augmented reality; interaction
• Next Generation Digital Infrastructure, networks (5G, IoT), distributed systems, cloud computing
• Computer science for biology and health
• foundations of computer science

ERC Advanced grant for Joris Van der Hoeven

Oana goga wins the 2023 lovelace-babbage prize, idia day, september 14th, program, sautos (safe autonomous systems) summer school, saclay, october 23-27 2023, icst phd day, june 2023, palaiseau, csdai best phd thesis for 2023.

Institut Polytechnique de Paris

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Research Masters and PhD tracks

In addition to the multidisciplinary training of excellence that constitutes the engineering cycle, ENSAE Paris offers more academic and disciplinary training, oriented towards research and the preparation of a PhD. These courses are run jointly with the partner schools within the Institut Polytechnique de Paris (IP Paris).

• The Master's programs, which are two-year courses, allow students to go deeper into one of the proposed disciplinary fields, with a view to research. ENSAE Paris student-engineers have the opportunity to enter directly into the second year of the Master's program.
• The PhD Track programs, selective and individualized 5-year courses, allow students to build a personalized pathway oriented towards their thesis topic from the beginning of their Master's degree, under the direction of a tutor and in immersion in cutting-edge research laboratories. ENSAE Paris student-engineers have the opportunity to enter directly into the second year of the PhD Track.

Set up within the Institut Polytechnique de Paris, these programs are operated jointly by the École Polytechnique, ENSTA Paris, ENSAE Paris, Télécom Paris, Télécom SudParis and other partner establishments such as HEC Paris, CentraleSupélec or the Université Paris-Saclay. More than 70 Masters and PhD tracks are offered in many fields: Biology, Physics, Mechanics, Applied Mathematics, Energy, Economics, Computer Science, Sociology, etc. You can find details of the courses (pedagogical objectives, laboratories and associated partners) and all information relating to admissions on the dedicated presentation pages.

The Masters programs in which ENSAE Paris is involved cover the following disciplines: economics, data science, statistics, finance and sociology.

The research courses in partnership, and compatible with the 3rd year of the ENSAE engineering cycle, are

• Master in Economics
• Master Statistics, Finance and Actuarial Science
• Master Data science  
• Master Mathematics of Randomness - Statistics & Machine Learning track
• Master Mathematics, Vision and Learning  
• Master Mathematics for Life Sciences
• Master Quantitative Sociology and Demography  
• Master Random Modelling and Data Science
• PhD Track Data Science and Artificial Intelligence
• PhD Track in Economics
• Phd Track Mathematics

Course of the dual education

ENSAE Paris student-engineers can follow the dual curriculum with the Master's degree in parallel with the third year of the engineering cycle. For ENSAE Paris, this dual education in the engineering cycle and in the Master's or PhD Track is facilitated by the organization of part of the courses in common, by agreements on the organization of the course (when the courses are not operated directly by ENSAE Paris) and by the way in which the education is carried out in the third year of the engineering cycle, where Mondays and Thursdays are free of classes. Finally, under certain conditions, the end-of-studies internship in the third year of the engineering cycle can be shared with the Master's thesis.

Application

All student-engineers apply directly to the Institut Polytechnique de Paris. The list of academic and linguistic prerequisites is available on each of the Masters presentation pages.

For ENSAE Paris student-engineers, applications are generally made during the second year of the engineering cycle, between January and April. For Polytechnic students who enter ENSAE Paris directly in the third year of the engineering cycle and who are interested in this double degree, applications are made independently of the application to ENSAE Paris.

Admissions for the 2022-2023 academic year will take place in three sessions for the master's programs, the first of which will begin on November 23 and end on February 9, 2022. Applications for the PhD tracks will take place in a single admission session from November 23, 2021 to January 27, 2022.

• Admissions for the year 2022-2023 will take place in three sessions for master's degrees, the first beginning on November 23 and ending on February 9, 2022
• Applications for PhD tracks will take place in a single admission session from November 23, 2021 to January 27, 2022
• Access to the application platform

Financing of tuition fees

Scholarships based on social criteria may be awarded. Applications must be made at the time of registration for the IP Paris Master's program, each year, using the student social file (DSE) to be completed online. The conditions of attribution are those stated on the DSE website.

Once the student social file has been completed online (Master's program / armed forces accreditation / 1st or 2nd year / Institut Polytechnique de Paris) and validated by the CROUS, registration with the Institut Polytechnique de Paris validates the file and triggers the payment of grants.

For further information, please contact [email protected]

• PhD student
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By clicking on continue , you will visit the website of École Polytechnique, one of the founding schools of Institut Polytechnique de Paris.

By clicking on continue , you will visit the website of ENSTA Paris, one of the founding schools of Institut Polytechnique de Paris.

By clicking on continue , you will visit the website of ENSAE Paris, one of the founding schools of Institut Polytechnique de Paris.

By clicking on continue , you will visit the website of Télécom Paris, one of the founding schools of Institut Polytechnique de Paris.

By clicking on continue , you will visit the website of Télécom SudParis, one of the founding schools of Institut Polytechnique de Paris.

• Applied Mathematics and Statistics Program

Master Year 2 Data Science

WHY ENROLL IN THIS PROGRAM?

Asset n° 1 .

Master key tools and skills for data scientists based on an interdisciplinary approach

Lay the foundations of your future career by pursuing a PhD track in Data Science

Open up numerous job opportunities as data scientists, data analysts, or in academia

• Description

Today, major players in the world of business are increasingly aware of the potential of their data and are looking for ways to extract as much useful information as possible. Data scientists are in charge of retrieving, storing, organizing, processing this mass of information to create value. This is a hybrid profile requiring a solid background in mathematics and statistics, mastery of data management and processing tools and infrastructure, as well as curiosity and a thirst to understand.

The objective of the Master in Datascience is to train experts in this field. At the end of the training, the students have acquired skills in mathematics of statistical learning, in deep learning, reinforcement learning, optimization, and big data infrastructures among others. In particular, these skills are developed through practical projects and data science competitions.  At the end of the year, both the results at the chosen courses and the professional project are evaluated to validate the Master. 

This program allows students to:

• become experts on statistical learning and artificial intelligence
• gain a comprehensive training in the various disciplines constituting data science, with a strong emphasis on the mathematics and statistics methodology
• master sophisticated techniques both theoretically and in practice

Data Science has a strong impact on many sectors. There is currently a large worldwide shortage of data scientists and data analysts. Students from Data Science and Big Data courses are therefore eagerly awaited on the global job market. Like all fields of breakthrough innovation (e.g. biotechnology and e-medicine), there is a high need for high-level engineers and doctoral candidates.

On average, almost 25% of the students pursue with a PhD, while the others pursue in the industry.

42 ECTS of courses to validate over the 3 quarters

18 ECTS for internship

Students of the Master can choose various courses, from very theoretical and mathematically involved courses, to more practical ones. In broad terms, the courses cover*:

• Convex optimization 
• Reinforcement learning 
• Graphical Models 
• Deep Learning
• Theory of Deep Learning 
• Machine Learning Theory 
• Machine Learning for Audio, Text, Graph, Dynamical Data
• Markov Chain Monte Carlo methods 

The courses also cover**:

• Large scale machine learning/ Big Data 
• (Advanced) Optimization
• Machine Learning & advanced methods
• Business or ethical aspects of ML 

*quite similarly to the MVA Master

** more specific to the Master Data Science - examples in (3) that are not covered by the MVA Master : Time Series, Causal Inference, Tail Event Analysis...

Large Scale Machine Learning/Big Data

Optimization

Machine Learning 

Machine Learning

Business and ethical aspects of ML

Large Scale Machine Learning

Business and Ethical Aspects of ML 

• Internship of minimum 16 weeks
• From April to end of August

Admission requirements

Academic prerequisites.

Completion of the first year of a Master in mathematics at Institut Polytechnique de Paris or equivalent in France or abroad.

Language prerequisites

How to apply.

Applications can be submitted exclusively online. You will need to provide the following documents:

• Two academic references (added online directly by your referees)
• Statement of purpose

You will receive an answer in your candidate space within 2 months of the closing date for the application session.

Fees and scholarships

Fees for 2023-2024 are :

• EU/EEA/Switzerland students: 4648€
• Non-EU/EEA/Switzerland students: 6839€
• Engineer students enrolled in one of the five member schools of Institut Polytechnique de Paris (Ecole polytechnique, ENSTA Paris, ENSAE Paris, Télécom Paris and Télécom SudParis): 159€
• Special cases: please refer to the "Cost of studies" section of the FAQs

Find out more about scholarships

Please note that fees and scholarships may change for the following year.

Applications and admission dates

Coordinators.

Rémi Flamary

Program Office 

Stéphanie Clevenot

Contact the Master Program Office

General enquiries

[email protected]

• UFR Droit Economie Management
• UFR Médecine
• UFR Pharmacie
• UFR Sciences
• UFR Sciences du Sport
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• ENS Paris-Saclay
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• Polytech Université Paris-Saclay
• Accessibility

M2 Data Sciences

• Entry requirements

Le S3 est dédié à la mise en place des outils et concepts de l'apprentissage et du machine learning. Le seul module obligatoire est le Data Camp. Les autres modules sont à la carte.

Le S4 permet l'approfondissement théorique et la mise en oeuvre applicative. Le stage est obligatoire, les autres modules sont à la carte.

When and where the solar eclipse will be crossing the U.S.

A total solar eclipse will grace the skies over North America on Monday, one of the most hotly anticipated sky-watching events in recent years.

Weather permitting , millions of people in Mexico, 15 U.S. states and eastern Canada will have the chance to see the moon slip between Earth and sun, temporarily blocking the sun’s light .

The total solar eclipse will be visible along a “path of totality” that measures more than 100 miles wide and extends across the continent. Along that path, the moon will fully obscure the sun, causing afternoon skies to darken for a few minutes.

Follow live updates on the solar eclipse

In all other parts of the continental U.S., a partial solar eclipse will be visible, with the moon appearing to take a bite out of the sun. Exactly how big a bite depends on the location.

The first spot in North America that will experience totality on Monday is on Mexico’s Pacific coast at around 11:07 a.m. PT, according to NASA .

After moving northeast across Mexico, the eclipse’s path travels through Texas, Oklahoma, Arkansas, Missouri, Illinois, Kentucky, Indiana, Ohio, Pennsylvania, New York, Vermont, New Hampshire and Maine. Slivers of Michigan and Tennessee will also be able to witness totality if conditions are clear.

In Canada, the eclipse will be visible in parts of southern Ontario, Quebec, New Brunswick, Prince Edward Island and Cape Breton, at the eastern end of Nova Scotia.

The timing of the eclipse and the duration of totality varies by location. Most places will experience around 2 minutes of darkness, but the longest periods of totality are typically in the center of the eclipse’s path.

This year, the longest stretch of totality will last 4 minutes and 28 seconds in an area northwest of Torreón, Mexico.

Below is a list of timings for some U.S. cities along the path of totality, according to NASA .

• Dallas: Partial eclipse begins at 12:23 p.m. CT and totality at 1:40 p.m. CT.
• Idabel, Oklahoma: Partial eclipse begins at 12:28 p.m. CT and totality at 1:45 p.m. CT.
• Little Rock, Arkansas: Partial eclipse begins at 12:33 p.m. CT and totality at 1:51 p.m. CT.
• Poplar Bluff, Missouri: Partial eclipse begins at 12:39 p.m. CT and totality at 1:56 p.m. CT.
• Paducah, Kentucky: Partial eclipse begins at 12:42 p.m. CT and totality at 2:00 p.m. CT.
• Carbondale, Illinois: Partial eclipse begins at 12:42 p.m. CT and totality at 1:59 p.m. CT.
• Evansville, Indiana: Partial eclipse begins at 12:45 p.m. CT and totality at 2:02 p.m. CT.
• Cleveland: Partial eclipse begins at 1:59 p.m. ET and totality at 3:13 p.m.
• Erie, Pennsylvania: Partial eclipse begins at 2:02 p.m. ET and totality at 3:16 p.m. ET.
• Buffalo, New York: Partial eclipse begins at 2:04 p.m. ET and totality at 3:18 p.m.
• Burlington, Vermont: Partial eclipse begins at 2:14 p.m. ET and totality at 3:26 p.m. ET.
• Lancaster, New Hampshire: Partial eclipse begins at 2:16 p.m. ET and totality at 3:27 p.m.
• Caribou, Maine: Partial eclipse begins at 2:22 p.m. ET and totality at 3:32 p.m. ET.

Other resources can also help you figure out when the various phases of the eclipse will be visible where you live, including NationalEclipse.com and TimeandDate.com .

If you plan to watch the celestial event, remember that it’s never safe to look directly at the sun, including through binoculars, telescopes or camera lenses. Special eclipse glasses are required to safely view solar eclipses and prevent permanent eye damage.

Denise Chow is a reporter for NBC News Science focused on general science and climate change.

US News & World Report Releases 2024 Rankings Of America’s Best Grad Schools

Texas A&M University is one of the nation’s leaders in graduate education, according to the latest rankings from U.S. News & World Report.

The university has 33 programs in the Top 50 spanning across agriculture, business, computer science, education, health, law, political science, public affairs, psychology, science, and veterinary medicine. U.S. News announced this week that the release of rankings for engineering, medical and clinical psychology will be delayed.

In its Best Graduate Schools ranking, the publication placed 10 of Texas A&M’s graduate programs in the Top 20; among those, six are Top 10:

College of Arts and Sciences

• Industrial and organizational psychology, No. 7 (No. 6 public)
• Inorganic chemistry, No. 5 (No. 2 public, No. 1 in Texas)
• Nuclear physics, No. 7 (No. 6 public, No. 1 in Texas)

School of Law, overall No. 26

• Dispute resolution, No. 5 (No. 3 public, No. 1 in Texas)
• Intellectual property, No. 6 (No. 2 public, No. 1 in Texas)

School of Veterinary Medicine and Biomedical Sciences, overall No. 10 (No. 9 public, No. 1 in Texas)

According to U.S. News , the rankings are based on expert opinion on program excellence and statistical indicators that measure the quality of a school’s faculty, research and students. Texas A&M currently enrolls 16,762 graduate and professional students (fall 2023), in more than 170 master’s, 94 doctoral and five professional degree programs.

“I’m so proud of our graduate students, the world-class faculty who mentor them and the outstanding programs that set them on a path to success in their chosen fields,” said Gen. (Ret.) Mark A. Welsh III, president of Texas A&M University. “Post-graduate education at Texas A&M contributes immeasurably to our research enterprise and our teaching and service missions. Congratulations to the students, faculty and staff whose work is reflected not just in rankings, but each and every day on our campuses and in the world at large.”

Texas A&M School of Law in Fort Worth, which has seen a remarkable rise in the U.S. News rankings, this year rose three spots overall, an increase of 57 spots in five years.

The Bush School of Government and Public Service, which ranks No. 26 overall in public affairs, has seen gains this round in non-profit management, up six places to No. 21. “The Bush School continues to make strides as a world-class Public Affairs school,” said Frank B. Ashley III, interim dean. “Employers know that graduates of our Public Service and Administration program are career-ready leaders with a passion for public service.”

Other notable rankings include:

• Analytical chemistry, No. 11 (No. 10 public)
• Applied mathematics, No. 13 (No. 6 public)
• Legal writing, No. 11 (No. 7 public, No. 1 in Texas)
• Marketing, No. 29 (No. 9 public)
• Management, No. 27 (No. 11 public)
• Statistics, No. 13 (No. 7 public, No. 1 in Texas)

View the full rankings for Texas A&M here and review the U.S. News methodology here .

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Machine Learning & Data Science Foundations

Online Graduate Certificate

Be a Game Changer

Harness the power of big data with skills in machine learning and data science, your pathway to the ai workforce.

Organizations know how important data is, but they don’t always know what to do with the volume of data they have collected. That’s why Carnegie Mellon University designed the online Graduate Certificate in Machine Learning & Data Science Foundations; to teach technically-savvy professionals how to leverage AI and machine learning technology for harnessing the power of large scale data systems.   

Computer-Science Based Data Analytics

When you enroll in this program, you will learn foundational skills in computer programming, machine learning, and data science that will allow you to leverage data science in various industries including business, education, environment, defense, policy and health care. This unique combination of expertise will give you the ability to turn raw data into usable information that you can apply within your organization.  

Throughout the coursework, you will:

• Practice mathematical and computational concepts used in machine learning, including probability, linear algebra, multivariate differential calculus, algorithm analysis, and dynamic programming.
• Learn how to approach and solve large-scale data science problems.
• Acquire foundational skills in solution design, analytic algorithms, interactive analysis, and visualization techniques for data analysis.

An online Graduate Certificate in Machine Learning & Data Science from Carnegie Mellon will expand your possibilities and prepare you for the staggering amount of data generated by today’s rapidly changing world. 

A Powerful Certificate. Conveniently Offered. 

The online Graduate Certificate in Machine Learning & Data Science Foundations is offered 100% online to help computer science professionals conveniently fit the program into their busy day-to-day lives. In addition to a flexible, convenient format, you will experience the same rigorous coursework for which Carnegie Mellon University’s graduate programs are known. 

For Today’s Problem Solvers

This leading certificate program is best suited for:

• Industry Professionals looking to deliver value to companies by acquiring in-demand data science, AI, and machine learning skills. After completing the program, participants will acquire the technical know-how to build machine learning models as well as the ability to analyze trends.
• Recent computer science degree graduates seeking to expand their skill set and become even more marketable in a growing field. Over the past few years, data sets have grown tremendously. Today’s top companies need data science professionals who can leverage machine learning technology.   

At a Glance

Start Date May 2024

Application Deadlines Rolling Admissions

We are still accepting applications for a limited number of remaining spots to start in Summer 2024. Apply today to secure your space in the program.

Program Length 12 months

Program Format 100% online

Live-Online Schedule 1x per week for 90 minutes in the evening

Taught By School of Computer Science

Request Info

Questions? There are two ways to contact us. Call 412-501-2686 or send an email to  [email protected]  with your inquiries .

Program Name Change

To better reflect the emphasis on machine learning in the curriculum, the name of this certificate has been updated from Computational Data Science Foundations to Machine Learning & Data Science Foundations.

Although the name has changed, the course content, faculty, online experience, admissions requirements, and everything else has remained the same. Questions about the name change? Please contact us.

Looking for information about CMU's on-campus Master of Computational Data Science degree? Visit the program's website to learn more.  Admissions consultations with our team will only cover the online certificate program.

A National Leader in Computer Science

Carnegie Mellon University is world renowned for its technology and computer science programs. Our courses are taught by leading researchers in the fields of Machine Learning, Language Technologies, and Human-Computer Interaction. 

Number One  in the nation for our artificial intelligence programs.

Number One  in the nation  for our programming language courses.

Number Four  in the nation for the caliber of our computer science programs.