Mit Mini Masters Data Science – Demand for professionals skilled in data, analytics and machine learning is exploding. In its mission to advance education, it has partnered with MITx to develop a micromaster’s program in statistics and data science.
Join over 1,000 certificate holders worldwide who have completed a micro-masters program in statistics and data science, mastering the art of data analysis. More than 480,000 unique students worldwide are enrolled in MM SDS courses covering the four pillars of data science: probability, statistics, machine learning, and computational data analysis.
Mit Mini Masters Data Science
There is an effective SDS Curriculum team that oversees and manages the program, from teachers and lecturers to day-to-day operations. All courses are rigorously taught by MIT faculty, including Nobel laureates, MacArthur Genius Grantees at the MIT level.
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Students who successfully complete the SDS Micromaster’s program have the opportunity to apply to MIT’s doctoral program in Social and Engineering Systems (SES). Students who are accredited in SES can expect their micro-masters program courses to be recognized with credit towards the relevant SES majors and requirements.
Learn about additional track schools and programs that offer credits to fast-track your master’s degree.
It is open to anyone, there is no application process and no formal prerequisites. College-level computing and comfort with mathematical logic and Python programming are highly recommended
Learn about the benefits of MicroMasters in Statistics and Data Science from Director Professor Munzer Dahleh:
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Enroll in the MITx MicroMasters Program for Statistics and Data Science to get more information about courses, capstone exams, calendar start and end dates, additional program benefits, and reviews of frequently asked questions.
MIT Institute for Data, Systems and Society 77 Massachusetts Avenue Cambridge, MA 02139-4307 | 617-253-1764 In four online courses developed by MIT faculty and delivered by edX, students learn, apply, and learn data analysis techniques and machine learning algorithms.
The new MITx Micro-Masters Program in Statistics and Data Science, which opened for enrollment today, helps online students develop their skills in the growing field of data science. The program provides students with a quality, professional introduction to MIT, while offering an MIT or other academic pathway to a master’s degree.
“There are many online programs that offer a professional overview of data science, but they don’t offer the level of benefit that students get from a real residential master’s program,” said MIT professor and program faculty member Debrat Shah. Department of Electrical Engineering and Computer Science (EECS). “This new micromaster’s program in statistics and data science brings the quality, rigor, and residency of a master’s-level program in data science at MIT to a broad international audience and at a very affordable cost that makes people do it. Learn while waiting for their day job.”
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A total of seven universities, Rochester Institute of Technology (USA), Doane University (USA), Galileo University (Guatemala), Reykjavík University, will receive the new MicroMaster Statistics and Data Science (SDS) master’s certification. (Iceland), Curtin University (Australia), Deakin University (Australia) and RMIT University (Australia).
“This high-quality, affordable online program prepares students to become data science professionals, building lasting careers and gaining hands-on experience. “Recipients of the MicroMasters credential will be able to solve complex problems with data and bring value to their organizations,” said Digital Learning’s Krishna Rajagopal. The program helps bridge the gap between adequate supply and demand for data scientists. “
In the year With courses starting in fall 2018, this new micromaster’s program combines theory and practice to provide students with a fundamental understanding of the methods and tools used in data science, as well as training in data analysis and machine learning. Through four online courses developed by MIT faculty and delivered by edX, students learn, apply, and learn data analysis techniques and machine learning algorithms.
The rigor of the new MicroMasters program is important, Shah said: “You can read all the blog posts about self-driving cars or any other aspect of data science, but that doesn’t get you thinking about the strengths and weaknesses of the technology.” Limitations. You need a rigorous and structured learning environment that helps you learn things carefully. The value of any academic institution is to summarize the historical background and key ideas, present them in a meaningful way so that students can consider them carefully and help people to be fully prepared for real-world challenges. “
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IDSS director Munzer Dahleh, an EECS professor at MIT, believes the new SDS program can be a model for other data science programs. “This new micromaster’s program in statistics and data science brings a data, systems, and society perspective to how education in statistics and data science should be viewed,” he said. We hope that other universities will adopt this new program as a basis for their master’s program in data science. “
Probability: The Science of Uncertainty and Information: An Introduction to Basic Random Processes and Statistical Foundations of Probability Models. The content of this course is similar to the corresponding MIT class—a course that has been offered for over 50 years and is continually refined. This class allows students to apply the tools of probability theory to real-world applications or to their research and is taught by John Siticalis, EECS Professor Clarence J. Label teaches.
Data Analysis in the Social Sciences: Introduces students to the concepts of probability and statistics, including techniques in modern data analysis: estimation, regression and econometrics, forecasting, experimental design, randomized control trials (and A/B testing), machine learning, and data. . The visual class illustrates these concepts with real-world examples and applications drawn from frontier research and is taught by Esther Duflo, Abdul Laf Jamiel MIT Professor of Poverty Reduction and Development Economics, and Sarah Fisher Ellison Senior Lecturer. Department of Economics
Basics of Statistics: Statistics is the science of turning vast amounts of “raw” data into insights that support better decisions. Basic statistical principles are at the forefront of recent advances in machine learning, data science, and artificial intelligence. The course will be taught by Philippe Rigolet, an associate professor in MIT’s Department of Mathematics and a member of the Center for Statistics and Data Science.
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Machine Learning in Python – From Linear Models to Deep Learning: Machine learning seeks to design and understand computer programs that learn from experience to predict or control. Machine engineering algorithms are employed by search engines, recommender systems, advertisers, and financial institutions for content recommendations by predicting consumer behavior, compliance, or risk. The course was taught by Delta Electronics professors Regina Barzilai and Tommy S. Zacola of EECS.
Thomas Siebel is a professor of electrical engineering and computer science at the Institute for Information, Systems and Society.
“The challenge in data science is that we want to make decisions from data,” says Shah. So we need smart and skilled people to build the information infrastructure to support informed decision making. ” The new MicroMasters in Statistics and Data Science program, which opened for enrollment today, will prepare the in-demand data scientists who will build that sustainable data infrastructure.
The Micro Master’s Program in Statistics and Data Science Certificate allows students to earn academic credit at seven universities around the world, making the certificate a pathway to a master’s degree. Loan amount and acceptance criteria are based on each institution. For more information, visit the program’s website
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The MicroMasters in Statistics and Data Science certificate allows students to earn academic credit at seven universities around the world, making the certificate a pathway to a master’s degree. Loan amounts and acceptance criteria depend on each institution.The following seven schools have created 19 different pathways.
Rochester Institute of Technology (USA): The Master of Science in Professional Studies offers students the opportunity to draw on courses offered in RIT graduate programs. Students
The Micromaster’s Certificate in Statistics and Data Science can be applied for at any time during the year and, if accepted, awards one-third of the credit hours required for the degree.
Doane University (USA): Upon admission to the Doane MBA program, the Statistics and Data Science Micromasters complete one-third of the credit hours required for the Master of Business Administration degree.
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Micromasters in Statistics and Data Science Acquiring the equivalent of one year of total graduate credits to complete a master’s degree in data science.
The MicroMasters has the potential to earn a quarter of the total graduate credits toward completing a Master of Computer Science in Statistics and Data Science. Reykjavík University offers business school certificate holders
A micromaster in statistics and data science can earn up to one-third of the total graduate credits for subsequent completion.
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