Statistics and Data Science
Program Information
About this Program
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.
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 three methods-centered courses and a domain analysis course to provide you with foundational knowledge and hands-on training in a discipline of your choice. All learners complete the Probability and Machine Learning courses. The track you choose determines your third methods course and a final domain analysis course.
All tracks are taught by MIT faculty and administered by IDSS at a similar pace and level of rigor as an on-campus 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.
What you'll learn
- Master the foundations of data science, data analysis, statistics, and machine learning.
- Analyze big data and make data-driven predictions through probabilistic modeling and statistical inference; identify and deploy appropriate modeling and methodologies in order to extract meaningful information for decision making.
- Develop and build machine learning algorithms to extract meaningful information from seemingly unstructured data; learn popular unsupervised learning methods, including clustering methodologies and supervised methods such as deep neural networks.
- Understand the interplay between statistics and computation for the analysis of real data.
- Finishing this MicroMasters program will prepare you for job titles such as: Data Scientist, Data Analyst, Business Intelligence Analyst, Systems Analyst, Data Engineer.
Courses
To complete this program, you must take 1 course.
Tracks: Complete 1 out of 4
Meet your instructors
Sara Fisher Ellison
Senior Lecturer
Sara Fisher Ellison is a Senior Lecturer in the MIT Economics Department. She was an undergraduate at Purdue University and received graduate degrees from both Cambridge University and MIT. She has been a fellow at both the Institute for Advanced Study and the Hoover Institute. Her recent research has investigated a number of questions in industrial organization, with a focus on the pharmaceutical industry and ecommerce. She serves on a number of editorial boards. She has taught at the undergraduate, MBA, and Ph.D. levels, and has received awards for both outstanding teaching and pedagogical innovation. To learn more, please click here.
