MITx MicroMasters in Data Science and Statistics: Which track is for me?
Want to advance your skills in statistics and data science without committing to a master's degree? The MIT MicroMasters® Program in Statistics and Data Science could suit your goals. Explore the program's four tracks and who they're best for.
By: Amy Boyington, Edited by: Rebecca Munday
Published: August 19, 2025
The MIT MicroMasters Program in Statistics and Data Science offers four tracks — General, Methods, Social Sciences, and Time Series and Social Sciences — each designed to advance specific analytical skills. At least one of these tracks may align with how you want to work with data, whether you want to apply data science across industries or focus on a more specific discipline, such as uncovering insights in social systems.
Learn what each track entails to choose the path that best fits your career interests and goals.
Why earn an MITx MicroMasters in Statistics and Data Science?
Build foundational knowledge
Learn core concepts like data analysis and machine learning that you can build upon with further education or training.
Develop targeted skills
Choose one of four tracks to build expertise in the methods, tools, and models most relevant to your desired career.
Get a degree
Earn a MicroMasters Program credential to apply to a master's program, reducing the time it will take to earn your degree.
MITx MicroMasters Program: Statistics and Data Science tracks
MIT's MicroMasters Program in Statistics and Data Science offers four tracks with slightly different curricula. Here's what you need to know to choose between them.
General
The General Track introduces key concepts in data analysis and data science for those seeking broad and versatile skills for virtually all industries. You'll build a foundation in probability, statistics, and machine learning. This track prepares you to contribute to data-driven decisions in fields like business and healthcare.
This track includes the following 15-17-week courses and a four-week capstone, for a completion time of 17 months:
- Probability - The Science and Uncertainty of Data
- Machine Learning with Python: from Linear Models to Deep Learning
- Fundamentals of Statistics
- Data Analysis: Statistical Modeling and Computation in Applications
Methods
The Methods Track lasts one year and five months and explores time series analysis, statistics, and machine learning fundamentals. This track is ideal for learners who want a deeper understanding of statistical methods used to support evidence-based decisions.
You'll complete a four-week capstone and the following courses in this track, each lasting 14-17 weeks, for a total completion time of 17 months:
- Probability - The Science and Uncertainty of Data
- Machine Learning with Python: from Linear Models to Deep Learning
- Fundamentals of Statistics
- Learning Time Series with Interventions
Social sciences
In the Social Sciences Track, you'll focus on analysis methods for making sense of real-world data, such as social trends and economic shifts. Curious thinkers who want to explore how data shapes society to tackle social, cultural, and policy-related issues might choose this track.
The Social Sciences Track takes 14 months to complete, with three 15-17-week courses, a four-week social sciences data analysis assessment course, and a capstone. Courses include:
- Probability - The Science and Uncertainty of Data
- Machine Learning with Python: from Linear Models to Deep Learning
- Fundamentals of Statistics
- Data Analysis in Social Science - Assessing Your Knowledge
Time series and social sciences
The Time Series and Social Sciences Track blends coursework from the Methods and Social Sciences tracks. You'll discover how to apply time series analysis to social, cultural, and policy data to uncover trends and patterns over time. This track is a strong fit for those pursuing roles in economics, public policy, or social research, such as economic data scientist or policy analyst.
This is the shortest track, with a completion time of 13 months. In addition to a four-week capstone, you'll complete a four-week social sciences data analysis assessment course and the following three courses, each lasting 14-16 weeks:
- Probability - The Science and Uncertainty of Data
- Machine Learning with Python: from Linear Models to Deep Learning
- Learning Time Series with Interventions
- Data Analysis in Social Science - Assessing Your Knowledge
Get started on edX
Learn statistics and data science with the MicroMasters Program in Statistics and Data Science. edX offers all four tracks, so you can sign up for the one that aligns with your desired career path.