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Statistics and Data Science

Massachusetts Institute of Technology via edX Micromasters


Demand for professionals skilled in data, analytics, and machine learning is exploding. The U.S. Bureau of Labor Statistics reports that demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026. Data scientists bring value to organizations across industries because they are able to solve complex challenges with data and drive important decision-making processes. Not only is there a huge demand, but there is a significant shortage of qualified data scientists with 39% of the most rigorous data science positions requiring a degree higher than a bachelor’s.

This MicroMasters program in Statistics and Data Science is comprised of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science, and hands-on training in data analysis and machine learning. You will dive into the fundamentals of probability and statistics, as well as learn, implement, and experiment with data analysis techniques and machine learning algorithms. This program will prepare you to become an informed and effective practitioner of data science who adds value to an organization. The program certificate can be applied, for admitted students, towards a PhD in Social and Engineering Systems (SES) through the MIT Institute for Data, Systems, and Society (IDSS) or may accelerate your path towards a Master’s degree at other universities around the world.

Anyone can enroll in this MicroMasters program. It is designed for learners that want to acquire sophisticated and rigorous training in data science without leaving their day job but without compromising quality. There is no application process but college-level calculus and comfort with mathematical reasoning and Python programming are highly recommended if you want to excel. All the courses are taught by MIT faculty at a similar pace and level of rigor as an on-campus course at MIT. This program brings MIT’s rigorous, high-quality curricula and hands-on learning approach to learners around the world – at scale.

For more detail on this program and credit pathways, please visit


Courses under this program:
Course 1: Probability - The Science of Uncertainty and Data

Build foundational knowledge of data science with this introduction to probabilistic models, including random processes and the basic elements of statistical inference -- Part of the MITx MicroMasters program in Statistics and Data Science.

Course 2: Data Analysis in Social Science—Assessing Your Knowledge

Learn the methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest, and then assess that knowledge-- Part of the MITx MicroMasters program in Statistics and Data Science.

Course 3: Fundamentals of Statistics

Develop a deep understanding of the principles that underpin statistical inference: estimation, hypothesis testing and prediction. -- Part of the MITx MicroMasters program in Statistics and Data Science.

Course 4: Machine Learning with Python: from Linear Models to Deep Learning

An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. -- Part of the MITx MicroMasters program in Statistics and Data Science.

Course 5: Capstone Exam in Statistics and Data Science

Solidify and demonstrate your knowledge and abilities in probability, data analysis, statistics, and machine learning in this culminating assessment. -- Final Requirement of the MITx MicroMasters Program in Statistics and Data Science.


Taught by

Jimmy Li, Jagdish Ramakrishnan, Katie Szeto, Kuang Xu, Regina Barzilay, Zied Ben Chaouch, Dimitri Bertsekas, Sara Fisher Ellison, Esther Duflo, Tommi Jaakkola, Philippe Rigollet, Jan-Christian Hütter, John Tsitsiklis, Patrick Jaillet, Karene Chu, Eren Can Kizildag and Qing He

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