Machine Learning in Business

Course starts 28 October 2020

Course information

Registration Closes:
20 October 2020
Course Starts:
28 October 2020
6 weeks, excluding orientation
6–8 hours per week, self paced learning online
USD $3,200
Payment Options
MIT Sloan School of Management


Machine learning offers an opportunity to gain a powerful competitive edge in business, and is increasingly becoming a priority for managers and executives.

In this online short course, you’ll be guided to discover the business potential of machine learning, while developing strategies for effective implementation.

This course focuses on the managerial implications of machine learning, while touching on certain technical aspects, in order to provide you with the deeper knowledge needed to craft an effective machine learning integration strategy.


Download course prospectus

What will set you apart

On completion of this course, you’ll walk away with:

  • A practical action plan to strategically implement machine learning in business
  • Exposure to the technical elements of machine learning, enabling you to leverage this technology, without needing to code or program
  • Insights from esteemed MIT Faculty and machine learning experts

Is this course for you?

Although not technical in focus, this online short course will be useful for leaders and decision-makers who want to gain a grounding in machine learning in order to successfully integrate it into their organization.

It’s also relevant for managers, data specialists, consultants, and business professionals interested in exploring the technology’s strategic implications. You’ll walk away with a sound understanding of the applications of machine learning in business, without needing to code or program. You’ll also explore the opportunities, capabilities, and scope of this transformative technology.

Course curriculum

Craft a practical integration strategy for machine learning and its many business applications as you work through the weekly modules of this online course.

  • Orientation module Welcome to your Online Campus
  • Module 1 Introduction to machine learning
  • Module 2 Implementing machine learning in a business
  • Module 3 Sensing the physical world
  • Module 4 Helping machines to learn to use language
  • Module 5 Finding patterns in human transactions
  • Module 6 Machine learning challenges and future

Join the evolution of business

This online program is delivered in collaboration with GetSmarter. Learn from industry thought leaders as you discover the evolving ways in which machine learning is benefitting business in this online short course from MIT Sloan and MIT CSAIL. 

Your Faculty Directors

The design of this online program is guided by MIT Faculty, as well as industry experts, who will share their experience and in-depth knowledge with you throughout the course.

Thomas Malone


Patrick J McGovern (1959) Professor of Management, and Founding Director of the MIT Center for Collective Intelligence


Thomas Malone is a professor of information technology and of organizational studies at the MIT Sloan School of Management, and his research focuses on how new organizations can be designed to take advantage of the possibilities provided by information technology.

He has published his groundbreaking research in the book The Future of Work and in over 100 articles, research papers, and book chapters. His newest book, Superminds, appeared in May 2018. He holds 11 patents, cofounded three software companies, and is quoted in numerous publications such as Fortune, the New York Times, and Wired.

Malone holds a BA from Rice University, two master’s degrees and a PhD from Stanford University, as well as degrees in applied mathematics, engineering-economic systems, and psychology.


Daniela Rus


Director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)


Daniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. She serves as the director of the Toyota-CSAIL Joint Research Center and is a member of the science advisory board of the Toyota Research Institute.

Rus’s research interests are in robotics, mobile computing, and data science. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, and a member of the National Academy of Engineering and the American Academy of Arts and Sciences. She is the recipient of the 2017 Engelberger Robotics Award from the Robotics Industries Association. She earned her PhD in computer science from Cornell University.

MIT Faculty

Erik Brynjolfsson

Erik Brynjolfsson

Professor, MIT Sloan Director, MIT Initiative on the Digital Economy

Catherine Tucker

Catherine Tucker

Sloan Distinguished Professor of Management, MIT Sloan

Antonio Torralba

Antonio Torralba

Professor, MIT CSAIL

Jim Glass

Jim Glass

Senior Research Scientist, MIT CSAIL

Andrew Lo

Andrew Lo

Director of the Laboratory for Financial Engineering, MIT Sloan

Alex ‘Sandy’ Pentland

Alex ‘Sandy’ Pentland

Founding Faculty Director of MIT Connection Science

Sinan Aral

Sinan Aral

David Austin Professor of Management, MIT Sloan

Joshua Tenenbaum

Joshua Tenenbaum

Paul E. Newton Career Development Professor of Cognitive Science and Computation, MIT CSAIL

Jeanne W. Ross

Jeanne W. Ross

Principal Research Scientist, MIT Sloan

Stefanie Jegelka

Stefanie Jegelka

Assistant Professor, MIT CSAIL

Earn a certificate of completion from MIT Sloan

Learn to incorporate machine learning into your business strategy and earn an official certificate of completion from the MIT Sloan School of Management. 

This machine learning program also counts towards an MIT Sloan Executive Certificate, which you can earn by completing four programs; three from your chosen certificate track and one completed in person. Find out more.

Your certificate will be issued in your legal name and sent to you upon successful completion of the program, as per stipulated requirements.


When do I start?

Our next available short course starts 28 October 2020.

Get More Information

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Still have a question? These may help


    GetSmarter's learning model is designed to help you, as a working professional, improve your skills without compromising on work and family responsibilities. The course work is broken up into weekly, manageable bite-sized modules, with incremental deadlines, designed to help you pace yourself over the duration of the course and allow you the legroom to work when it suits you best.

    At the beginning of each week you'll be presented with all the lectures, notes and assignments necessary for completion. You also have access to your Success Advisor who will help you set goals and track key milestones, manage your time, and field any administrative requests you might have.


    By improving your skills and industry knowledge, you'll be having an influence on the success of your organisation.

    Why wouldn't you ask your boss to help you fund your studies if it's going to have an impact on the way you do business?

    37% of our past students receive financial assistance from their employers. You can ask for help, too. Here is a guide to show you how to receive financial assistance from your employer.


    The Online Campus will be your virtual classroom for the duration of your course. Through its easy-to-use interface you'll have access to a diverse variety of course content formats, including: interactive video lectures, module notes, practice quizzes, Prezis, assignment briefs, and additional web resources.

    On the Online Campus, you'll also be able to ask questions and interact with your fellow students and Head Tutor through the Online Campus discussion forums. If you're experiencing tech issues or need advice from your personal Success Advisor, you can use the Online Campus to get in touch.