EXECUTIVE EDUCATION

Machine Learning: From Data to Decisions

Join MIT's online program to harness the power of machine learning

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Course Dates
STARTS ON

TBD

Course Duration

DURATION

8 weeks, online
6-8 hours per week

Course Duration

PROGRAM FEE

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Note: This is not a coding course, but rather an introduction to the many ways that machine learning tools and techniques can help make better decisions in a variety of situations.

Who is this Program for

Participants will gain a practical understanding of the tools and techniques used in machine learning applications. In the MIT tradition, you will learn by doing. There are no prerequisites in terms of math or computational science, although some experience with introductory-level statistics is helpful.

Representative job functions and titles include:

  • CEOs and Managing Directors
  • CIOs and Chief Data Officers
  • Directors of Digital Solutions
  • Directors of Innovation
  • EVPs of Technical Solutions
  • Business Intelligence Managers
  • Data and Analytics Managers
  • Heads of Analytics
  • Senior Delivery Managers
  • Program Managers
  • Solution Architects
  • Data Scientists

Participant Testimonials

"I understand how data scientists work and can interact with them more effectively."

— Fabrice Testa, CEO, Premium Head Ventures

"I'll implement Machine Learning into our current projects, enable new capabilities, and drive further innovation opportunities."

— Koray Sonmezsoy, Chief Technology Officer, Caravel Group

"The program had a great balance of theoretical explanations and live examples…showing a more systematic way of analyzing problems."

— Navaneetha Krishnan, Deputy Finance Manager, Ford

Your Learning Journey

This online program takes a look at machine learning through a lens of practical applications. It is designed specifically for professionals who want to develop a competitive edge by turning what is unknown into what’s known—leading to better decisions and outcomes.

Machine Learning: Building Blocks

Program Modules

Module 1:

Introduction and Overview of Machine Learning

Module 2:

Understanding Your Data

Module 3:

Prediction Part 1 – Regression

Module 4:

Prediction Part 2 – Classification

Module 5:

Prediction Part 3 – Neural Networks

Module 6:

Decision Making Foundations

Module 7:

Decision Making Applications

Module 8:

Causal Inference

Module 1:

Introduction and Overview of Machine Learning

Module 5:

Prediction Part 3 – Neural Networks

Module 2:

Understanding Your Data

Module 6:

Decision Making Foundations

Module 3:

Prediction Part 1 – Regression

Module 7:

Decision Making Applications

Module 4:

Prediction Part 2 – Classification

Module 8:

Causal Inference
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What You’ll Learn

Machine learning is a collection of models, methods, and algorithms to help make better decisions that are driven by data, not gut feelings or guesswork. The tools and techniques in this machine learning program can help to address many common challenges. Learn with examples from:

Banking

How do you predict whether a borrower will default on a loan?

Pharmaceutical

When developing new drugs, how can you design better experiments to know if a new drug will be more effective than an existing one?

Marketing

How do you know which marketing channel is performing best, and what is the interaction effect when you are using multiple channels?

Retail

To optimize your inventory, how do you know whether to pull from a distribution center or a retail store to fulfill an online order?

Finance

How are data scientists exploring ways to predict the future price of digital assets, such as Bitcoin?

Ecommerce

How do you decide when to cross-market vs. upsell a customer at checkout—what drives more revenue?

Faculty

Devavrat Shah Faculty

Devavrat Shah

Professor, Department of Electrical Engineering and Computer Science; Director of Statistics and Data Science Center, Massachusetts Institute of Technology

Devavrat Shah is a professor with the department of electrical engineering and computer science at MIT. He is a member of the Laboratory for Information and Decision Systems (LIDS) and Operations Research Center (ORC), and the Director of the newly formed Statistics and Data Center in Institute for Data, Systems, and Society. His research focus is on theory of large complex networks, which includes network algorithms, stochastic networks... More info

Certificate

Certificate

Get recognized! Upon successful completion of the program, MIT Professional Education grants a certificate of completion to participants. This program is scored as a pass or no-pass; participants must receive 80 percent to pass and obtain the certificate of completion.

Participants will be awarded 6.4 continuing education units towards professional development.

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Note: After successful completion of the program, your verified digital certificate of completion will be E-mailed to you in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of MIT Professional Education.

Still Have Questions?

  • How do I know if this program is right for me?

    This program is not a program to learn how to code, but rather an introduction to the many ways that machine learning tools and techniques can help you make better decisions in a variety of situations. The program is organized into four key building blocks: Understanding Data; Prediction; Decision Making; and Causal Inference.

    • Representative industries include engineering, data science, IT, software, strategy, media, healthcare, manufacturing and business intelligence
    • Program is designed for both technical and non-technical professionals. If you aspire to become a data scientist, have some experience with data science, or plan to work with a team of data scientists, this program will be beneficial for understanding the tools and techniques to help make sense of the data
    • Functional and cross-functional teams are encouraged to attend together, to accelerate the machine learning adoption process

    Are there any prerequisites for this program?

    There are no prerequisites in terms of math or computational sciences, however some experience with introductory-level statistics is helpful.


    What is the typical class profile?

    MIT’s online programs draw professionals from around the globe, from every industry imaginable, and from a wide variety of functional backgrounds. This program is designed for both technical and non-technical professionals, so we expect it to be both diverse and very well attended, given the popularity of machine learning initiatives.


    What are the learning requirements for passing this program?

    This program is scored as a pass or no-pass; participants must receive 80% to pass and obtain the certificate of completion from MIT Professional Education directly. Elements that contribute to the score are the assessments (which can be completed multiple times, if needed) and the application exercises.


    Are there continuing education units offered?

    Yes! This program offers 6.4 continuing education units. To learn more about continuing education units visit MIT Professional Education’s website.

  • How much time is required each week?

    You will need to dedicate between 6-8 hours per week. You can expect to devote a few hours to watching the video lectures, an hour for contributing to discussion boards and reflecting on your learning, an hour for assessments and live faculty webinars held on certain weeks, and 1-2 hours for application exercises, which are not assigned every week. There will also be a resource library on the learning platform for you to access additional machine learning resources at your convenience.


    What is it like to learn online with MIT?

    It’s interactive, flexible, and designed to include personal attention so that you can reach your learning goals more effectively. Participants are highly encouraged to contribute to the discussion boards to enhance their own learning, and to enhance the learning of others. It’s a community of learners who are generally excited to share and grow their knowledge. Here are a few elements that make it unique:

    • There will be live sessions with MIT faculty with Q&A, so that you can get your questions answered in real time
    • Program facilitators monitor the discussion boards to keep things moving along and offer insights and advice. These are individuals with deep domain expertise and help supplement the knowledge from the recorded videos and live teaching sessions
    • Live office hours are offered regularly throughout the program to address questions or ask for clarification on the learning concepts
    • Application exercises are done individually for this program and each participant can choose whichever best meets one’s skills and personal goals

    Can I interact with MIT faculty directly?

    Yes, through live webinars you will be able to ask questions in real time. In addition, there are content experts who moderate the discussion boards, which is an essential element to facilitate learning for you and your peers from around the world.


    When are the live faculty sessions scheduled for?

    Because participants join from different time zones all over the world, we strive to offer the live sessions at times when the vast majority of participants would be able to join. Typically, that would be between 8 am and 10 am ET, with announcements going out a few days/weeks ahead of time for a live session. All sessions are recorded, so if you are unable to attend live, you will receive a link to the recording. Moderated discussion boards are designed to supplement the live sessions.


    How do I interact with other program participants?

    We believe that peer learning adds to the overall experience substantially. You can connect and communicate with other participants through our learning platform. You will be able to form interest groups or location-specific groups and interact among those groups. You will also be able to message another participant directly.

  • What do I receive upon successful completion of the program?

    Upon successful completion of the program, you will receive a certificate of completion from MIT Professional Education. This program is scored as a pass or no-pass; participants must receive 80% to pass and obtain the certificate of completion. Elements that contribute to the score are the assessments (which can be completed multiple times, if needed) and the application exercises.

    You will receive a digital certificate approximately two weeks after your successful completion of the program, once scoring is complete.

    You will also be eligible to receive 6.4 continuing education units from MIT Professional Education. To learn more about continuing education units visit MIT Professional Education’s website.


    Can I get the hard copy of the certificate?

    No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, Twitter, etc.


    Do I receive alumni status after completing this program?

    No, however you can receive 6.4 continuing education units from MIT Professional Education upon successful completion of the program, plus a certificate of completion directly from MIT Professional Education.


    How long will I have access to the learning materials for?

    You will have access to the online learning platform and all the videos and program materials for 1 full year following the program start date. This information is intended only for registered participants and access to the learning platform is restricted only to that individual per the terms of agreement.

  • What equipment or technical requirements are there for this program?

    Participants would need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access content such as documents, spreadsheets, presentations, PDF files, and transcripts.


    Do I need an active internet connection to access the program content?

    Yes, the learning platform is accessed via the internet and video content is not available for download. You can download files of video transcripts, assignment templates, readings, etc. however, the video lectures must be streamed via the internet.

  • What is the program fee and what forms of payment do you accept?

    • The program fee can be seen at the top of this page and payment is accepted only in US dollars.
    • Payment can be made online through credit/debit cards: Visa, MasterCard, and Amex

    What if I don’t have a credit card – is there another mode of payment accepted?

    Yes, you can do the bank remittance in USD via wire transfer. Please contact your Program Advisor for more details.


    Is there an option to make flexible payments for this program?

    Yes, the flexible payment option allows a participant to pay the program fee in installments. This option is made available in the payment form and should be selected before making the payment.


    Does the program fee include taxes? Are there any additional fees?

    Yes, the program fee is inclusive of any taxes with the exception of GST for Singapore residents.

  • Withdrawals and Refunds

    You may request a full refund up to 7 days of your payment or 14 days after the program commences, whichever comes later. If your enrollment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to: admissions@emeritus.org


    Deferrals

    After a cohort commences, you can request to change to a future cohort of same program within 50% of program completion. A deferral request must be submitted along with a selected reason and explanation. Cohort changes may be made only once per enrollment and is subject to availability of other cohorts scheduled at our discretion. This will not be applicable for deferrals within the refund period and the limit of one deferral per enrollment remains. All deferral requests should be sent to: admissions@emeritus.org

Apply Now

Early registrations are encouraged. Seats fill up quickly!