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 54% of the most rigorous data science positions requiring a degree higher than a bachelor’s.

This MicroMasters® program in Statistics and Data Science (SDS) was developed by MITx and the MIT Institute for Data, Systems, and Society (IDSS). It is a multidisciplinary approach comprised of four separate tracks with four online courses each and a virtually proctored exam. Each track focuses on a combination of methods-centered courses and domain analysis courses to provide you with foundational knowledge and hands-on training. All learners complete the Probability and Machine Learning courses, two other courses determined by the chosen track, and the Capstone Exam.

General Track
This track will prepare you to become an informed and effective practitioner of data science who adds value to your organization across industries.

Explore the General track here

Methods Track
This track will prepare you with in-depth knowledge of data science and time series analysis and will enable you to conduct rigorous analysis, inform decision-making processes, and contribute to evidence-based practices across industries.

You are currently exploring the Methods track

Social Sciences Track
This track will prepare you to extract meaningful insights from social, cultural, economic, and policy-related data and equip you to tackle complex real-world problems and contribute to cutting-edge advancements in AI and data-driven solutions within all social sciences.

Explore the Social Sciences track here

Time Series and Social Sciences Track
This track will equip you to analyze the impact of interventions on time series data, preparing you for roles in economics, public policy, and social sciences where understanding temporal dynamics is crucial for informed decision-making and policy formulation.

Explore the Time Series and Social Sciences track here

All tracks are taught by MIT faculty and administered by IDSS at a similar pace and level of rigor as an on-campu

To earn the MicroMasters program certificate in Statistics and Data Science, learners must complete and successfully earn a certificate in the four required courses and pass a virtually-proctored capstone exam.

MicroMasters programs are designed to offer learners a pathway to an advanced degree and can count as credit toward completing a Master’s degree program. Learners who successfully earn this MicroMasters program certificate may apply for admission to several Master’s programs, and if accepted, the MicroMasters program certificate will count towards the degree.

Learners who successfully complete this MicroMasters program certificate have the opportunity to apply to the MIT Doctoral Program in Social and Engineering Systems (SES) offered through the MIT Institute for Data, Systems, and Society (IDSS).

Learners can use their MicroMasters program certificate to demonstrate their preparation in Statistics and Data Science fundamentals to the SES Admissions Committee. Learners admitted to SES can expect that their MicroMasters coursework will be recognized with credit for corresponding SES core classes, and for satisfying the SES Information, Systems, and Decision Science requirements. More information on the MIT SES Doctoral Program can be found here.

In addition, learners who successfully earn the MicroMasters program certificate in Statistics and Data Science are now eligible to earn credit at a number of universities across the globe to fast track their pursuit of a full Master’s degree. A list of pathways to graduate programs can be found here.

s course at MIT. The program is designed for learners who 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.

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