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Get updates & access a FREE case study from this course

Take a sneak peek at the case study used in this course and learn to build your own recommendation engine. Complete the form below:

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Data Science and Big Data Analytics: Making Data-Driven Decisions

Turn big data into even bigger results with a seven-week online course from MIT.

Get updates & access a FREE case study from this course

By submitting your information, you are agreeing to receive periodic information about online programs from MIT related to the content of this course.

Make better data-driven business decisions

Could you be using data more effectively?

90% of the world’s data has been created in just the past few years. Faced with overwhelming amounts of data, organizations are struggling to extract the powerful insights they need to make smarter business decisions. To help uncover the true value of your data, MIT Institute for Data, Systems, and Society (IDSS) created the online course Data Science and Big Data Analytics: Making Data-Driven Decisions for data scientist professionals looking to harness data in new and innovative ways.

Over the course of seven weeks, you will take your data analytics skills to the next level as you learn the theory and practice behind recommendation engines, regressions, network and graphical modeling, anomaly detection, hypothesis testing, machine learning, and big data analytics.

At the end of this course you will receive a digital Professional Certificate and 1.8 Continuing Education Units (CEUs) from MIT.

MIT Faculty explain the impact of big data on business decision making.

After this course, you will be able to:

Don't just discover new strategies, tools, and insights - put them to the test! With a selection of 20 case studies and hands-on projects, this course helps learners apply their newfound knowledge to realistic business challenges.

Although Python is the most frequently used language, R can be used to complete many of the case studies. Both of required case studies in this course can be completed with either Python or R.  View the week-by-week course schedule.

The MIT xPRO Learning Experience

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What learners and companies are saying

More than 6,000 professionals have completed this course.

Murali Thyagarajan

Murali Thyagarajan - DBA & Application Support, Nasdaq

"The course was easy to understand and had depth. All the concepts were clearly laid out and explained. This is the best course I have come across on this topic."

Jasmine Latham

Dr. Jasmine Latham - Lead Data Scientist at ONS Data Science Campus

"I am very pleased with the course content, it is exactly the level I am looking for. Each professor/course presenter has packed a lot of information and has explained complex algorithms in good detail. Some with [a] good sense of humor."

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Adnan Raza - Business Consulting, Mackenzie Investments

"As a novice student in the field of AI and Machine learning, the module based approach really helped me structure the step-wise approach. In addition the real world examples helped associate concepts with applications. I am now more aware and equipped compared to Day 1."

Anonymous Learner Profile Avatar

Sunil Upadhyay - Tech Lead, IBM

"I had very basic information about data sciences and machine learning when I started this course. This course has definitely helped in getting an overview of different aspects and algorithms for data analysis and processing and to gather insights out of it."

MIT FACULTY TEACHING THIS COURSE

Devavrat-Shah-Co-Director-120x120_c

Devavrat Shah

Professor, Department of Electrical Engineering & Computer Science; Director, Statistics and Data Sience Center

Philippe-Rigollet

Philippe Rigollet

Associate Professor, Mathematics Department at MIT

Victor-Chernozhukov-1

Victor Chernozhukov

Professor, Department of Economics and the Statistics and Data Science Center at MIT

Stefanie-Jegelka-Finalpng

Stefanie Jegelka

Associate Professor, Department of Electrical Engineering and Computer Science and member of Computer Science and AI Lab and IDSS

Ankur-Moitra

Ankur Moitra

Associate Professor, Department of Mathematics and member of the Computer Science and AI Lab at MIT

Tamara-Broderick

Tamara Broderick

Associate Professor, Department of Electrical Engineering and Computer Science and a member of the Computer Science and AI Lab at MIT

David-Gamarnik-square-1

David Gamarnik

Nanyan Technological University Professor, Sloan School of Management

Jonathan-Kelner

Jonathan Kelner

Associate Professor, Department of Mathematics and a member of the Computer Science and AI Lab at MIT

Kalyan Veeramachaneni

Kalyan Veeramachaneni

Principal Research Scientist at the Laboratory for Information and Decision Systems at MIT

Caroline-Uhler

Caroline Uhler

Associate Professor, Department of Electrical Engineering and Computer Science at MIT and IDSS

Guy-Bresler-120x120_c-1

Guy Bresler

Associate Professor, Department of Electrical Engineering & Computer Science, Laboratory for Information and Decision Systems and IDSS

Who Should Enroll

Professionals at any career stage, looking to turn large volumes of data into actionable insights.


Past learners' job roles have included: business intelligence analysts, management consultants, technical managers, business managers, data science mangers.


Data science enthusiasts and IT professionals.


Background knowledge of statistical techniques and data calculations or quantitative methods of data research is strongly recommended.


Familiarity with either R or Python is recommended but not required.

JUSTIFY YOUR PROFESSIONAL DEVELOPMENT

Many companies offer professional development benefits to their employees but sometimes starting the conversation is the hardest part of the process.

Use these talking points, stats, and email template to advocate for your professional development through MIT xPRO's online course, Data Science and Big Data Analytics.

Ready for a sneak peek?

Sample the case study.

Ever wonder how companies like Netflix, Spotify and Pandora filter products based on their unique user’s preference?

In this case study, you will learn how Netflix utilizes Recommendation Engines to provide the best possible shows and movies for unique users.

To access this case study, submit your information in the form above. 

Propel Your Career On Your Terms

Technology is accelerating at an unprecedented pace causing disruption across all levels of business. Tomorrow’s leaders must demonstrate technical expertise as well as leadership acumen in order to maintain a technical edge over the competition while driving innovation in an ever-changing environment.

MIT uniquely understands this challenge and how to solve it with decades of experience developing technical professionals. MIT xPRO’s online learning programs leverage vetted content from world-renowned experts to make learning accessible anytime, anywhere. Designed using cutting-edge research in the neuroscience of learning, MIT xPRO programs are application focused, helping professionals build their skills on the job.

Embrace change. Enhance your skill set. Keep learning. MIT xPRO is with you each step of the way.

Have questions about the course?