Professional Certificate Program in Machine Learning & Artificial Intelligence

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.

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.

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.

Electives

• Advanced Data Analytics for IIOT and Smart Manufacturing — $3900 (4 days)
  Core strategies and frameworks for using data driven analysis, simulation, automation, and optimization techniques to improve manufacturing processes and deploy IIoT systems.
• Advanced Reinforcement Learning—$2,500 (2 days)
  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. 
• AI for Computational Design and Manufacturing—$4,700 (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.
• AI in Robotics: Learning Algorithms, Design and Safety—$3,750 (3 days)
  Explore breakthrough advances in robot learning, safety certification, and testing—and acquire the advanced knowledge you need to create state-of-the-art generative AI applications.
• AI Strategies and Roadmap: Systems Engineering Approach to AI Development and Deployment—$4,200 (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.
• AI System Architecture and Large Language Model Applications —$4,750 (5 days)
  Deepen your understanding of the end-to-end AI system architecture needed to design and deploy large language models (LLMs)—and implement an LLM application of your own during a hands-on group project.
• Applied Data Science Program: Leveraging AI for Effective Decision-Making—$3,900 (5 day equivalent)
  In this live 12-week live virtual program, you’ll upgrade your data analytics skills by deep learning the theory and practical application of supervised and unsupervised learning, time-series analysis, neural networks, recommendation engines, regression, and computer vision.
• 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.
• Deep Learning for AI and Computer Vision—$3,760 (4 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.
• 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 Mathematics for Artificial Intelligence—$2,500 (2 days)
  Take a deep dive into the mathematical foundations of AI and machine learning. You’ll explore the math behind not only fundamental models and algorithms, but also recent innovations such as Transformers and Graph Neural Nets—and discover how these concepts relate to Python code and associated applications.
• Graph Algorithms and Machine Learning—$2,500 (4 half-days)
  This accelerated course provides a comprehensive overview of critical topics in graph analytics, including applications of graphs, the structure of real-world graphs, fast graph algorithms, synthetic graph generation, performance optimizations, programming frameworks, and learning on graphs. 
• Machine Learning for Healthcare—$3,200 (3 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.
• Machine Learning for Materials Informatics—$3,600 (4 days)
  Explore the cutting-edge of modern material informatics tools, including machine learning, data analysis and visualization, and molecular/multiscale modeling.
• Reinforcement Learning—$3,600 (3 days)
  Join professionals from around the world to upgrade your machine learning (ML) toolkit in this three-day RL BootCamp.
• Workplace Analytics, AI, and Ethics—$3,750 (3 days)
  Explore the innovative management strategies, AI technologies, and workplace analytics tools that are transforming the way companies do business. Over three intensive days, you’ll build an understanding of these breakthrough technologies and their ethical implications and learn how to use them to boost employee productivity, streamline workloads—and help your enterprise meet its most ambitious goals.

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.

Links & Resources

• Reinventing the neural net chip for local analytics, ILP Institute Insider, August 14, 2018
• Interview: Vivienne Sze, associate professor of electrical engineering and computer science at MIT, insideBIGDATA.com, December 13, 2017
• Building the hardware for the next generation of artificial intelligence: Class taught by Vivenne Sze and Joel Emer brings together traditionally separate disciplines for advances in deep learning. MIT News, November 30, 2017
• How neural networks think: General-purpose technique sheds light on inner workings of neural nets trained to process language. MIT News, September 8, 2017
• Bringing neural networks to cellphones. MIT News, July 18, 2017
• Putting data in the hands of doctors: Computer scientist Regina Barzilay empowers cancer treatment with machine learning. MIT News, February 16, 2017
• Energy-friendly chip can perform powerful artificial-intelligence tasks. MIT News, February 3, 2016

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

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

How to Apply

The professional certificate program application fee is $325 (non-refundable). To apply, submit an application for the program by selecting the Apply Today button, 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.

Each of the courses you select will be paid at the per-course rate. Visit our course catalog for individual course information.

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

Location

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.