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.
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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.
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.
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.
You are currently exploring the General track
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.
Explore the Methods track here
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-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's inside
Four courses
Probability - The Science of Uncertainty and Data
(192 hours)
Probability - The Science of Uncertainty and Data
(192 hours)
Machine Learning with Python: from Linear Models to Deep Learning
(180 hours)
Machine Learning with Python: from Linear Models to Deep Learning
(180 hours)
Fundamentals of Statistics
(204 hours)
Fundamentals of Statistics
(204 hours)
Data Analysis: Statistical Modeling and Computation in Applications
(200 hours)
Data Analysis: Statistical Modeling and Computation in Applications
(200 hours)Learning objectives
- 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.
- 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.
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