Earn this prestigious professional credential by completing five short courses within two consecutive summers. Submit your application, along with a non-refundable $325 application fee, to get started.

About MIT Professional Education 

For 70 years, MIT Professional Education has been providing technical professionals worldwide a gateway to renowned MIT research, knowledge, and expertise, through advanced education programs designed specifically for them. In addition to industry-focused, two-to-five-day live virtual and on-campus courses through Short Programs, MIT Professional Education offers professionals the opportunity to take online and blended learning courses through Digital Plus Programs, attend courses abroad through International Programs, enroll in regular MIT academic courses through the Advanced Study Program, or attend Custom Programs designed specifically for their companies. For more information, please visit professional.mit.edu.

Testimonials

Master Cutting-Edge Strategies with Insights from MIT Experts

Navigate the shifting digital landscape and identify emerging opportunities for creating new value with the latest machine learning and artificial intelligence strategies from MIT.

Designed for professionals who work with data analysis and predictive modeling, our Professional Certificate program will help you master the concepts, formulations, models, and algorithms you need to get more from your current data strategies and embrace the latest frameworks and tools that are disrupting the industry. 

Accessibility

Accelerated Format. Individualized Instruction. Immediate Impact.

Going beyond lectures, the certificate courses include interactive discussions, group projects, and real-world case studies led by MIT faculty and experts.

MIT Professional Certificate Program in Machine Learning and Artificial Intelligence

Equip yourself to succeed in the AI-powered future.

In this program, you will: 

- Explore the latest data-driven approaches, including computer vision,        deep learning, and reinforcement learning.

- Develop the data analysis skills you need to overcome complex machine    learning challenges. 

- Master the AI tools, techniques, and algorithms reshaping the digital          landscape.

Certificate Teaching Team

Certificate Program Details

Earn the Professional Certificate by completing at least five qualifying courses, which must include four core courses, and at least one elective. You can customize your learning experience by selecting the elective that is most relevant to you and your organization.

How to Apply

To earn our Professional Certificate, you must complete 16 or more days of qualifying Short Programs courses within a 36-month period. Start by submitting your application, along with a non-refundable $325 application fee, using the link below. Once you’ve been accepted, you can apply for the two core courses and electives of your choice at a pace that suits your schedule. 

Upcoming Programs

Machine Learning for Big Data and Text Processing: Advanced
June 9 – 11, 2021
Course fee: $3,500
Led by Regina Barzilay, Tommi Jaakkola, Stefanie Jegelka
Acquire the entry-level machine learning expertise you need to immediately implement new strategies for driving value in your organization. 

Bioprocess Data Analytics and Machine Learning
June 28 – 30, 2021
Course fee: $3,500
Led by Richard D. Braatz, Brian Anthony, Seongkyu Yoon
Drive breakthroughs in your organization by taking advantage of revolutionary developments in bioprocess data analytics and machine learning. 

Designing Efficient Deep Learning Systems
June 28 – 29, 2021 
Course fee: $2,500
Led by Vivienne Sze
Discover how to build and utilize custom hardware for deep learning systems that extract meaningful information from large amounts of data. 

Machine Learning for Healthcare
June 14 – 15, 2021
Course fee: $2,500
Led by David Sontag
Gain practical strategies for overcoming some of today’s most pressing healthcare challenges by leveraging the power of Big Data.

Advanced Reinforcement Learning
June 28 – 30, 2021
Course fee: $3,650
Led by Pulkit Agrawal, Cathy Wu
Explore the cutting-edge of reinforcement learning research, and learn which approaches are best suited to solving your organizational challenges.

Deep Learning for AI and Computer Vision
July 19 – 23, 2021
Course fee: $5,500
Led by Antonio Torralba, Phillip Isola
Learn to build advanced computer vision applications by explore the latest developments in vision AI, with a focus on advanced deep learning methods.

Foundations of Data and Models: Regression Analytics
July 19 – 23, 2021
Course fee: $4,500
Led by F. Dale Morgan
Maximize the power of your advanced computing methods and identify optimal strategies for fitting your unique data to models.

Pulkit Agrawal is an Assistant Professor of Electrical Engineering and Computer Science at MIT and head of the Improbable AI Lab at MIT’s Computer Science and Artificial Intelligence Laboratory.

Brian Anthony is Director of MIT’s Master of Engineering in Manufacturing Program, Co-Director of the Medical Electronic Device Realization Center, and Deputy Director for the MIT Skoltech Initiative.

Richard D. Braatz is the Edwin R. Gilliland Professor of Chemical Engineering at MIT.

Philip Isola is an Assistant Professor in the Department of Electrical Engineering and Computer Science at MIT.

David R. Martinez is a Laboratory Fellow in the Cyber Security and Information Sciences Division at MIT Lincoln Laboratory.

F. Dale Morgan is a Professor of Geophysics in the Department of Earth, Atmospheric, and Planetary Sciences at MIT.

Justin Solomon is an Associate Professor of Electrical Engineering and Computer Science and Principal Investigator at MIT’s Computer Science and Artificial Intelligence Laboratory.

David Sontag is the Hermann L. F. von Helmholtz Career Development Professor in the Institute for Medical Engineering and Science and an Assistant Professor in the Department of Electrical Engineering and Computer Science at MIT.

Suvrit Sra is an Associate Professor in the Department of Electrical Engineering and Computer Science and a Principal Investigator in the Laboratory for Information and Decision Systems at MIT.

Vivienne Sze is an Associate Professor in the Department of Electrical Engineering and Computer Science at MIT.

Antonio Torralba is a Professor of Electrical Engineering and Computer Science and the MIT Director of the MIT-IBM Watson AI Lab.

Bernhardt L. Trout is the Raymond F. Baddour, ScD, (1949) Professor of Chemical Engineering and Director of the MIT Society, Engineering, and Ethics Program.

Cathy Wu is the Gilbert W. Winslow Career Development Assistant Professor of Civil and Environmental Engineering at MIT.

Seongkyu Yoon is a Professor in the Department of Chemical Engineering at MIT and the Ward Endowed Professor in Biomedical Sciences at UMass Lowell.

“Being part of the MIT ecosystem has put me ahead of the curve by providing access to the latest information, tools, and methodologies. The faculty are very helpful and truly want to see participants succeed.” 

- Renzo Zagni, Co-founder, Intelenz

“MIT equipped me with the knowledge that I needed to expand my participation in the machine learning and AI components of my industry.” 

- Peter Gathua, Founder, PMG Associates LLC

“The MIT Professional Education faculty members have great insight into what’s coming next in AI—and even what’s coming after that.” 

- Rick Durham, Data Science and AI Architect, Americas Global Black Belt Team, Microsoft

Equip yourself to succeed in the AI-powered future.

In this program, you will: 

- Explore the latest data-driven approaches, including computer vision, deep learning, and reinforcement learning.

- Develop the data analysis skills you need to overcome complex machine learning challenges. 

- Master the AI tools, techniques, and algorithms reshaping the digital landscape.

Certificate Core Instructors