https://professional-education.mit.edu/mlai-openhouse

MIT Professional Education is pleased to offer the Professional Certificate Program in Machine Learning & Artificial Intelligence. MIT has played a leading role in the rise of AI and the new category of jobs it is creating across the world economy. Our goal is to ensure businesses and individuals have the education and training necessary to succeed in the AI-powered future. This certificate guides participants through the latest advancements and technical approaches in artificial intelligence technologies such as natural language processing, predictive analytics, deep learning, and algorithmic methods to further your knowledge of this ever-evolving industry.

Overview

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 —$4,200 (4 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.

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