MITx MicroMasters Program in Statistics and Data Science announces new Data Analysis elective
New course focuses on hands-on applications of data analysis across disciplines
A new elective course in the MITx MicroMasters Program in Statistics and Data Science (SDS) offers an increased focus on applying data science to complex, real-world problems. Data Analysis: Statistical Modeling and Computation in Applications launches in Spring 2021, and is open for enrollment now.
Developed by MIT Institute for Data, Systems, and Society (IDSS) on the edX platform, the new course is a hands-on introduction to the interplay between statistics and computation for the analysis of real data. This elective lets learners apply data analysis methods to different domains, and offers a unique choice to help tailor their learning experience. Learners will apply fundamental analytic tools and methods on randomized control trials, hypothesis testing, linear regression, and principal component analysis. They’ll learn and implement common models and methods to analyze specific types of data in four different domain areas:
- Epigenetic codes and data visualization
- Criminal networks and network analysis
- Prices, economics, and time series
- Environmental data and spatial statistics
Increased options, deeper training
The MITx MicroMasters program offers a professional and academic credential for online learners from anywhere in the world. To earn the credential, learners must pass an integrated set of MIT graduate-level courses online and proctored exams online. Credential-holders can then apply for an accelerated master’s degree program at pathway universities around the world. The SDS MicroMasters program was launched in fall 2018, and there are currently 188 credential holders worldwide.
To complete the SDS MicroMasters Program, learners must take the three core courses, and one elective — choosing between 14.310Fx Data Analysis in Social Science — Assessing Your Knowledge, or the new elective course 6.419x Data Analysis: Statistical Modeling and Computation in Applications. Data Analysis in Social Science focuses on questions of cultural, social, economic, and policy interest, while the new elective covers data analysis methods and applications in science, networks, economics and industry. Once learners have passed their four courses (3 core +1 elective), they can take the virtually proctored Capstone exam to earn the MicroMasters credential in Statistics and Data Science.
“When we launched the MicroMasters program we had a strong focus on applications in the social sciences. Now we are offering a different course, which tries to provide exposure to a collection of data science applications,” says Prof. Devavrat Shah, director of the Statistics and Data Science Center at IDSS.
The course content was developed by course instructors Stefanie Jegelka and Caroline Uhler, both associate professors of Electrical Engineering & Computer Science. On campus, this course is the required capstone subject for the minor in Statistics and Data Science that is available to MIT undergraduates from any major. Karene Chu, research scientist and MITx Digital Learning Scientist, led the development of the online version for the MicroMasters program.
The instructors have prepared a series of real-world case studies to demonstrate the different ways hands-on data analysis intersects with different disciplines, and how those working in data analysis can help to advance the state of the art in some specific fields. Learners will use Python, R, and other software to perform full analysis and improve their data visualization and communication skills through written reports. They will discuss their methods and ideas with peers, and gain a sophisticated understanding of how to formulate questions and approaches to data analysis problems within their own areas of interest.
Says Chu, “Any learner who is interested in extracting information from data and making data-driven decisions, who has fundamental knowledge in statistics (such as covered in the Micromasters Program in Statistics and Data Science) and proficiency in programming, will benefit from this course.”
By enriching the curriculum and enhancing the data analysis pillar of the program, the team hopes to provide more flexibility for learners who may wish to focus on one or another of the many avenues of study in the complex world of data science.
“If we want to train data scientists really well, they need the same foundational pillars of knowledge, but we need to offer different options depending on one’s interests,” says Shah.
Note: If you have already purchased the MITx MicroMasters Program Bundle with the elective course 14.310Fx, you will need to contact our customer service team by December 7, 2020 if you wish to take the new 6.419x elective course instead.
Regina Barzilay -- Course Faculty for Machine Learning course in MicroMasters Program in Statistics and Data Science (MM SDS) -- wins $1M Association for the Advancement of Artificial Intelligence Squirrel AI award.
MIT professor announced as award’s first recipient for work in cancer diagnosis and drug synthesis.
Read the full story at MIT news!
We are excited to announce and share that MM SDS professor Regina Barzilay was awarded $1M by the Association for the Advancement of Artificial Intelligence Squirrel AI award. Professor Regina Barzilay is the first recipient of the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity.
For more than 100 years Nobel Prizes have been given out annually to recognize breakthrough achievements in chemistry, literature, medicine, peace, and physics. As these disciplines undoubtedly continue to impact society, newer fields like artificial intelligence (AI) and robotics have also begun to profoundly reshape the world.
In recognition of this, the world’s largest AI society — the Association for the Advancement of Artificial Intelligence (AAAI) — announced today the winner of their new Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity, a $1 million award given to honor individuals whose work in the field has had a transformative impact on society.
The recipient, Regina Barzilay, the Delta Electronics Professor of Electrical Engineering and Computer Science at MIT and a member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), is being recognized for her work developing machine learning models to develop antibiotics and other drugs, and to detect and diagnose breast cancer at early stages.
In February, AAAI will officially present Barzilay with the award, which comes with an associated prize of $1 million provided by the online education company Squirrel AI.
New Data Analysis Elective -- 6.419x Data Analysis: Statistical Modeling and Computation in Applications
The MicroMasters Program in Statistics and Data Science is excited to announce that starting Spring 2021, a new data analysis course---Data Analysis: Statistical Modeling and Computation in Applications, will become an additional offering as part of the MicroMaster Program in Statistics and Data Science.
This new course is a hands-on introduction to the interplay between statistics and computation for the analysis of real data. Learners will apply their fundamental knowledge on randomized control trials, hypothesis testing, linear regression, principal component analysis, and learn and implement common models and methods to analyze specific types of data in four different domain areas:
- Epigenetic Codes and Data Visualization
- Criminal Networks and Network Analysis
- Prices, Economics and Time Series
- Environmental Data and Spatial Statistics
Each module will have homework that will guide learners to analyze a real data set from the domain of focus. They will use python, R or other software of their choice to perform full analysis and improve their data visualization and communication skills through written reports in homeworks.
6.419x Data Analysis: Statistical Modeling and Computation in Applications will be an elective course in the MITx MicroMasters Program in Statistics and Data Science, juxtaposed against 14.310/14.310Fx Data Analysis for Social Scientists/Data Analysis in Social Sciences--Assessing your Knowledge. See here for more information on the course.
What this means is that to complete the SDS MicroMasters Program, learners will need to take the 3 core courses, and 1 elective; and for the elective, learners can choose either 14.310x Data Analysis in Social Science—Assessing Your Knowledge /14.310Fx Data Analysis in Social Science—Assessing Your Knowledge, or the new elective course 6.419x Data Analysis: Statistical Modeling and Computation in Applications. Once learners have passed their 4 courses (3 core +1 elective), they will then take the virtually-proctored Capstone exam to earn the MicroMasters in Statistics and Data Science credential.
The new data analysis elective will open to learners with its first run February 2021 - May 2021, with registration and exact course dates sometime in Fall 2020. Please check the MM SDS schedule and Dates FAQ page for future updates.
July 28, 2020
Online MM Completion Celebration Update
MIT Open Learning and the MicroMasters Statistics and Data Science Program (SDS) are proud to share with you the link below for our first MM Completion Celebration, which occurred virtually on June 18, 2020. After six months planning, we launched our first joint MM (PoM, DEDP, SDS) completion celebration. Close to 500 learners and their families watched the show live.
The event recording includes brief remarks from IDSS leaders and MIT faculty, including IDSS Director Munther Dahleh and MicroMasters Program in Statistics and Data Science Director Devavrat Shah. Also featured are a selection of MM SDS credential holders who have shared their experiences in the program.
Read all about the MM Completion Celebration here in this MIT News article, "Learners today, leaders tomorrow." You can also view on demand a video recording of the inaugural celebration here. Note — The SDS portion of the video begins at 23:54 through 38:46.
We are very proud of all learners and look forward to celebrating next years group!
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