Note: This online program requires no prerequisites in terms of math or computational sciences, although some experience with introductory-level statistics is helpful.
It’s a common challenge for organizations: how do we make optimal choices with so many unknown variables? It turns out that insights come from turning what is unknown into what is known. Using the tools and techniques that facilitate that process is how machine learning can deliver tremendous impact to your projects.
Corporate spending on AI and ML is forecast to grow from $12 billion in 2017 to $57.6 billion by 2021.
SOURCE: INTERNATIONAL DATA CORPORATION
61% of organizations picked machine learning/artificial intelligence as their company’s most significant data initiative for the next year.
SOURCE: MEMSQL SURVEY, 2018
The number of machine learning pilots and implementations will double in 2018 compared to 2017, and double again by 2020.
SOURCE: DELOITTE GLOBAL
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 basic understanding of statistics is helpful. 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.
Representative functions and industries of past participants include:
"I understand how data scientists work and can interact with them more effectively."
—Fabrice Testa, CEO
"I'll implement Machine Learning into our current projects, enable new capabilities, and drive further innovation opportunities."
—Koray Sonmezsoy, Chief Technology Officer
"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
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 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?
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
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.
It is part of the MIT culture for students and faculty to immerse themselves in their studies and research. Attending MIT is often likened to "drinking from a fire hose" of information. For those participants who display extraordinary efforts in exhibiting that MIT ethos and demonstrate leadership by going above and beyond in their program participation, they’ll be considered to receive the coveted MIT Professional Education Fire Hydrant Award. This award can be displayed in professional bios, such as on LinkedIn. Decisions are made by MIT faculty and the program team based on active participation and behaviors that exemplify leadership and contribution to the overall program experience for the cohort.
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.