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

Enroll Now
  • START DATE February 3, 2020
  • TIME COMMITMENT 4-5 hours per week
  • DURATION 7 weeks
  • FORMAT Online
  • PRICE $899


Could you be using data more effectively? Uncover your data’s true value and learn how to leverage it with the latest and most powerful tools, techniques, and theories in data science from industry experts and renowned MIT faculty. View the week to week course schedule here.

  • Apply data science techniques to your organization’s data management challenges.
  • Explore the latest trends in machine learning.
  • Convert datasets to models through predictive analytics.
  • Improve your business decision-making using analytical models.
  • Identify and avoid common pitfalls in big data analytics.
  • Deploy machine learning algorithms to mine your data.
  • Master best practices for experiment design and hypothesis testing.
  • Determine the difference between graphical models and network models.
  • Choose how to represent your data when making predictions.

Who Should Enroll

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

  • Past learner job roles have included: business intelligence analysts, management consultants, technical managers, business managers, data science managers.

  • Data science enthusiasts and IT professionals.

DSx Who Should Enroll.png

How You Will Learn

  • icon-innovate.png


    Practice processes and methods through simulations, assessments, case studies and tools, including the IBM Q experience.

  • icon6 - network.png


    Connect with an international community of professionals while working on projects based in real-world examples.

  • icon1 - work life balance.png


    Access all of the content online and watch videos on the go.

  • icon3 - feedback.png


    Bring your new skills to your organization, through examples from technical work environments and ample prompts for reflection.

  • icon5 - certificate.png


    Earn a Professional Certificate and 1.8 Continuing Education Units (CEUs) from MIT.

  • icon3 - trends or apply knowledge.png


    Gain insights from MIT faculty and industry experts.

What learners are saying

More than 7,000 professionals have completed this course.

Murali Thyagarajan.jpeg

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 …

Continue Reading
Adnan Raza.jpeg

Adnan Raza, Dir. Lead 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…

Continue Reading
Anonymous Learner Profile Avatar.png

Linnea Serzan, BPO Manager at Johnson & Johnson

My newly gained knowledge from this course will help me organize drive insights from data that we previously were not modeling or analyzing, or had t…

Continue Reading

MIT Faculty & Industry Experts

Meet your instructors

Devavrat Shah

Devavrat Shah

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

Philippe Rigollet

Philippe Rigollet

Associate Professor, Mathematics Department at MIT

Victor Chernozhukov

Victor Chernozhukov

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

Stefanie Jegelka

Stefanie Jegelka

Associate Professor, Department of Electrical Engineering & 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 Artificial Intelligence Lab at MIT

Tamara Broderick

Tamara Broderick

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

David Gamarnik

David Gamarnik

Nanyan Technical 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 & Computer Science and IDSS

Guy Bresler

Guy Bresler

Associate Professor, Department of Electrical Engineering & Computer Science LIDS and IDSS

The Best Companies Connect with the Best Minds at MIT

Deepen your team’s career knowledge and expand their abilities with MIT xPRO’s online courses for professionals. Develop customized learning for your team with bespoke courses and programs on your schedule. Set a standard of knowledge and skills, leading to effective communication among employees and consistency across the enterprise.

Find out what MIT xPRO can do for your team.

Inquire Now
B2B xPRO image.jpg