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MIT Adds Professional Education Programs in Machine Learning, AI

Academic programs are one way for professionals to stay current with today's most in-demand skills.

• By Brian J. Dooley
• May 1, 2018

With the skills shortage increasing and competition for talent raging through industry and among start-ups, training has become a priority. Many aspiring data professionals are sharpening their skills through online courses or attending industry conferences. However, sometimes you just want to go back to school, at least for a visit.

For Further Reading: 4 Proven Ways Newbie Analysts Can Become Machine Learning Pros Career Switch Q&A: Negotiating the Path to Data Engineer or Scientist To Be Successful with Machine Learning, Expect to Learn As You Go

Looking for a certificate in data science? Harvard offers one. A program in machine learning? Try the University of Washington or the University of California, Irvine. Although new programs are starting every year at schools around the world, one of the leaders in continuing education for advanced data techniques is MIT.

MIT has a venerable history of providing professional education -- more than 65 years. Today its Short Programs draw more than 1,500 students each summer to short courses across topics ranging from innovation and entrepreneurship to biotechnology, information technologies, data modeling, and systems engineering.

Its new slate of AI and machine learning courses for the coming summer will be appreciated by professionals in the global community who need to come up to speed as AI techniques are applied to an increasing array of disciplines.

MIT Short Programs Meet Industry Needs

According to its director, Lily Fu, "Short Programs is an extensive offering with over 50 courses and three professional certificates. Faculty work hard to get the latest practical angle for industries, with a focus on hands-on application. Participants don't just go to lectures but they get to practice the techniques and apply them immediately to their job. Courses are constantly updated with new relevant findings."

The overall aim of the program is to provide the tools for leaders and managers of professional departments to broaden their understanding of technologies to ensure that new technology can be adequately integrated into business processes.

"For those taking short courses, one of the benefits is direct access to full-time MIT faculty and experts in the area," says Fu. "We don't seek outside lecturers for these subjects; there are immediate opportunities for interacting with MIT's latest research."

In machine learning and artificial intelligence, businesses are interested in a wide range of possible interdisciplinary applications. "Leaders need to understand how machine learning is evolving, what AI is, what natural language processing is, what robotics is, and so forth," says Fu.

"The really important thing is understanding how the technology connects to their work. Many people in industry struggle to keep up with the extremely fast pace of technological innovation. The goal of MIT Professional Education is to separate the wheat from the chaff, helping people understand the big themes, how they relate to their own products and services, what they need to learn, and to acquire the broad set of skills needed to lead teams better and make better decisions."

Take, for example, the Modeling and Optimization for Machine Learning course offered by MIT Professors Justin Solomon and Suvrit Sra that reduces engineering and computational problems to their standard mathematical forms to determine which algorithms and software tools will best solve them. Because an important part of optimizing machine learning is developing the basic approach, modeling, optimization, and algorithm selection are critical to integrating deep learning and other machine learning into the business environment.

According to Justin Solomon, "We will take a group of professionals in areas related to data science, get them up to speed with modeling and optimization, and walk through common scenarios and modern tools. We will work with a range of machine learning models, and optimization tools. The basic structure will be a conversation about a particular optimization tool in the morning, application to a case, and then students will get a chance to work with what they have learned. We will lead the class through particular applications, examining optimization problems, experimenting with state-of-the-art tools, and developing an understanding that can be extended to computer vision, computational biology, language, modeling, and other areas familiar to machine learning."

By the end of the course, participants will be expected to be able to dissect real-world challenges, breaking them down to estimate the difficulties in designing a numerical solution.

Choosing a Program

Short Programs run for between one and five days and take place on MIT's campus in Cambridge, Mass. during the summer. Upon completion, participants receive an MIT Professional Education Certificate of Completion, continuing education units, and access to MIT Professional Education's extensive professional alumni network. In addition, there are three multicourse certificate programs that provide a more extensive learning experience, including the one in artificial intelligence and machine learning.

"Course selection is driven by faculty interest and market demand," says Fu. "MIT is at the frontier of technology. The value is to bring industry and academia together to hear from each other. Our students will be the industry leaders of the future. It is increasingly important for academia and technical industries to maintain a conversation as new technologies begin to influence the business and the world."

You might or might not be able to travel to Boston for the summer, but if you are considering any continuing education program, the principles that MIT adheres to in designing its courses are good to keep in mind. Read the descriptions of the classes or reviews from previous students, and try to determine: Does the program deal with real-world problems? Does it provide hands-on lessons or just lectures? Are the instructors experts in their fields?

Technology leaders within business and industry need to prepare for an emerging generation of intelligent processes and tools. That means keeping up to date with the latest research and keeping the lines of communication open between the academic world and your enterprise.