At IDSS, we believe that data has the potential to create change. With the right tools, organizations can use data to discover insights that drive real transformation. This is as true in industry as it is in society, where large, complex systems that affect the lives of many are producing massive amounts of data all the time.

That's why a fundamental piece of the IDSS mission is to advance education in statistics, machine learning, and applied data analysis. While these tools are a major pillar in our on-campus programs like TPP and SES, we are also developing new ways to bring this education outside of MIT.

I'm excited to share with you some stories and updates on those efforts, from our online courses and strategic partnerships in education to an exciting new look at getting the science of uncertainty more prominent in K-12 education. I am thankful for the teams behind these efforts, and inspired by the learners from around that world whose lives have already been impacted by this work.

Already that impact has come full circle, with one online learner from our Applied Data Science Program participating in our student-run Policy Hackathon as a member of a winning team. We look forward to engaging more with this broader community of practitioners, including credential holders of the IDSS MicroMasters Program in Statistics and Data Science who are interested in applying to our residential SES PhD program.

Munther Dahleh, Director

William A. Coolidge Professor, Electrical Engineering and Computer Science

Demand for professionals skilled in data, analytics, and machine learning is exploding. The MicroMasters Program in Statistics and Data Science (SDS) is comprised of four foundational pillars of Data Science: probability, statistics, machine learning, and computation of data analysis.

IDSS offers two online data science programs in collaboration with Great Learning, an online education service provider and IDSS alliance member. With a global footprint in over 140 countries, Great Learning offers career-relevant programs in high-demand domains.

With recorded lectures by MIT faculty and personalized mentorship from industry practitioners, this 10-week program covers statistics and Python foundations, machine learning, deep learning, NLP, prediction, recommendation systems, and more.