Awarded upon successful completion of 16 or more days of qualifying Short Programs courses in Professional Education, this certificate equips you with the best practices and actionable knowledge needed to put you and your organization at the forefront of the AI revolution.

How to Apply

To apply, submit an application for the program using the link below, along with a non-refundable $325 application fee. After you have been accepted into the program, you should then apply for the individual courses that you intend to take this year.

Registration is now open!

Key Benefits

The Professional Certificate Program in Machine Learning & Artificial Intelligence enables you to:

  • Learn in-person from renowned MIT faculty and leading industry practitioners
  • Learn essential concepts and skills needed to develop effective AI systems
  • Understand the challenges posed by AI in the workplace
  • Apply cutting-edge, industry-relevant knowledge in machine learning and AI
  • Network with an accomplished group of peers from around the globe

As an MIT Professional Education Professional Certificate Program alumnus you will:

  • Be eligible to earn Continuing Education Units (CEUs)
  • Receive a 15% discount on future MIT Professional Education Short Programs and Digital Plus Programs courses
  • Gain membership in the exclusive MIT Professional Education LinkedIn group
  • Receive a complimentary one-year subscription to the MIT Technology Review upon completion of the program
  • Obtain updates on faculty research, new programs, and MIT initiatives via our newsletter

Who Should Attend

The Professional Certificate Program in Machine Learning & Artificial Intelligence is designed for:

  • Professionals with at least three years of professional experience who hold a bachelor's degree (at a minimum) in a technical area such as computer science, statistics, physics, or electrical engineering
  • Anyone whose work interfaces with data analysis who wants to learn key concepts, formulations, algorithms, and practical examples of what is possible in machine learning and artificial intelligence
  • Managers who need the vision and understanding of the many opportunities, costs, and likely performance hurdles in predictive modeling, especially as they pertain to large amounts of textual (or similar) data
  • Professionals looking for a deeper understanding and hands-on experience with MIT faculty and industry experts

Why Study Machine Learning and Artificial Intelligence at MIT?

Machine learning is more than just algorithms: it requires math, statistics, data analysis, computer science, and programming skills. MIT is a hub of research and practice in all of these disciplines and our Professional Certificate Program faculty come from areas with a deep focus in machine learning and AI, such as the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL); the MIT Institute for Data, Systems, and Society (IDSS); and the Laboratory for Information and Decision Systems (LIDS).

The program allows individuals to interact with all these key disciplines. Leading MIT faculty experts will guide participants through the latest breakthroughs in research, cutting-edge technologies, and best practices used for building effective AI-systems. The program provides a well-rounded foundation of knowledge that can be put to immediate use to help people and organizations advance cognitive technology.


"As we dove deeper into the latest machine learning and AI technologies, the faculty kept us grounded with real-life examples. While the strategies were very complex, we always learned how to apply them in the real world."
Renzo Zagni, Founder and CEO, Intelenz

Certificate Requirements

The Professional Certificate in Machine Learning and Artificial Intelligence consists of a total of at least 16 days of qualifying courses. At least one of the Machine Learning for Big Data and Text Processing courses is required. Those with prior machine learning experience may start with the Advanced course, and those without the relevant experience must start with the Foundations course and also take the Advanced course. Participants must attend the full duration of each course. You may select any number of courses to take this year but all courses within the program must be completed within 36 months of your first qualifying course. 

  • Successful completion of 16 or more days of qualifying courses, including the required Machine Learning for Big Data and Text Processing course(s)
  • Courses primarily take place in June, July, and August on MIT's campus
  • Additional courses may be offered in other locations; please see individual course pages for details
  • Courses must be taken within 36 months
  • Non-refundable application fee: $325

Participants who have been accepted into the program prior to August 2019 will complete under the legacy program requirements, which consists of four qualifying courses, including the required Machine Learning for Big Data and Text Processing courses.


The professional certificate program application fee is $325 (non-refundable). Each of the courses you select will be paid at the per-course rate. Visit our course catalog for individual course information.

Core Courses

We recommend taking the two required courses first. However, if there are elective courses that you have the background and education to begin with you are welcome to do so. Please note that whether you begin with core or elective courses you are required to complete all requirements within 36 months.

  • Machine Learning for Big Data and Text Processing: Foundations⁠—$2,500 (2 days)
    Ensures those who are just getting started in the field know the core mathematical concepts and theories relevant to machine learning. You'll walk away with a solid understanding of probability, statistics, classification, regression, optimization. 
  • Machine Learning for Big Data and Text Processing: Advanced⁠— $3,500 (3 days)
    See how the latest tools, techniques and algorithms driving modern and predictive analysis can be applied in different fields: what kinds of problems they can/cannot solve and what issues are likely to arise in practical applications.

Note: MIT Professional Education's Short Programs is committed to providing a diverse and updated portfolio of Short Programs courses and reserves the right to change these course selections in future years.


  • Ethics of AI: Safeguarding Humanity— $3,200 (3 days)
    Examine today’s most pressing ethical issues related to AI and explore ways that organizations can leverage technology to benefit mankind.
  • Modeling and Optimization for Machine Learning— $4,700 (5 days)
    Reduce machine learning problems to their standard mathematical form and understand how to identify the best algorithms and software tools to solve them. Participants are required to have a background in linear algebra and multivariable calculus, as well as at least basic programming in Python.
  • AI for Computational Design and Manufacturing—$5,500 (5 days)
    Learn more about the new field of computational design, including advanced manufacturing hardware considerations, methods for creating digital materials, and generative design workflows.
  • Machine Learning for Healthcare—$2,500 (2 days)
    Explore machine learning methods for clinical and healthcare applications and how emerging trends will shape healthcare policy and personalized medicine. Participants of this course should be comfortable programming in Python, performing basic data analysis, and using the machine learning toolkit Scikit-learn.
  • Advanced Reinforcement Learning— $3,650 (3 days)
    A majority of the course will be dedicated to deep overviews into key topics in active research, including offline reinforcement learning, the theory of RL, multi-agent RL, Monte Carlo Tree Search, hierarchical RL, and model-based RL exploration. 
  • Deep Learning for AI and Computer Vision— $5,500 (5 days)
    Develop practical skills necessary to build highly accurate, advanced computer vision applications. Participants should have experience in programming with Python, as well as experience with linear algebra, calculus, statistics, and probability.
  • Bioprocess Data Analytics and Machine Learning—$3,500 (3 days)
    Discover transformative ways to apply data analytics and avoid the most common pitfalls that arise when analyzing bioprocess data.
  • Designing Efficient Deep Learning Systems— $2,500 (2 days)
    Discover how to overcome power, memory, and processing challenges to deploy complex deep learning neural networks on IoT-enabled devices such as cell phones, wearables, and drones. 
  • Foundations of Data and Models: Regression Analysis— $4,500 (5 days)
    Learn the fundamentals of fitting data to models using linear algebra, various computational methods, and other mathematical concepts.
  • Reinforcement Learning— $3,000 (3 days)
  • AI Strategies and Roadmap: Systems Engineering Approach to AI Development and Deployment— $3,950 (5 days)
    Acquire the skills and strategies you need to deploy an AI systems engineering approach that maximizes the value of your digital products and services.

Note: MIT Professional Education's Short Programs is committed to providing a diverse and updated portfolio of Short Programs courses and reserves the right to change these course selections in future years.

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Machine Learning Certificate -  Thumbnail Image


MIT is located in the intellectual, exciting, and vibrant city of Cambridge, Massachusetts, nestled next to the state capital of Boston and right on the Charles River. MIT is located in Kendall Square, an innovation hub with more startups than any other place in the world (for example, at CIC). Take time to visit historic Boston while here—catch a Red Sox game, go whale watching, visit world-class museums, take a boat ride on the Charles River, visit Quincy Market, or explore other local area colleges. TripAdvisor's Best of Boston Tourism list may be a good resource.