Driving Innovation with Generative AI

Unlock practical, cutting-edge generative AI skills to accelerate progress and propel your career with this 6-week course from MIT xPRO.

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  • START DATE September 29, 2025
  • TIME COMMITMENT 4-7 hours per week
  • DURATION 6 Weeks
  • FORMAT Online
  • CEUs 3
  • PRICE $2,979

UNLEASH THE POWER OF GENERATIVE AI

Generative AI is revolutionizing industries, unlocking new potential for creativity, efficiency, and innovation. By mastering the core technologies behind AI, you'll be equipped to enhance productivity, improve customer experiences, generate dynamic content, and drive breakthrough solutions.

In this course, you’ll gain hands-on experience with leading AI tools like DALL-E, Midjourney, ChatGPT, and more, applying them to real-world challenges. You’ll dive deep into the foundations of generative AI, exploring how these tools can be used to create visual and textual outputs, design collaborative agents, and tackle societal and ethical challenges. With guidance from MIT faculty and experts, you’ll be prepared to leverage these technologies to lead innovation in your field and navigate the complexities of this rapidly evolving landscape.

WHAT YOU WILL LEARN

View the week by week schedule here.

  • Gain a solid understanding of Generative AI and machine learning, focusing on neural networks and the role of data.
  • Explore the synergy between Generative AI and human creativity, emotion, and expression.
  • Develop the skills to work with image-generating models, understanding their components and evaluating key factors affecting their performance.
  • Learn to apply Generative AI in coding, design, and chemistry, mastering algorithms for molecular prediction, code generation, and structural design.
  • Analyze the evolution, limitations, and future potential of Large Language Models (LLMs) across various industries.
  • Understand the role of Pro-Human Generative AI in decision-making, addressing biases, and applying best practices in health and societal contexts.

WHO SHOULD ENROLL

  • Engineers working as Product Managers, Web Application Developers/Managers, Software Service (SaaS) professionals, UX/UI Designers, Solutions Architects

  • Technical professionals looking to understand the potential of generative AI in their careers in various fields

  • No prior background in analytics, computer science, coding, or machine learning is required. 

Who Should Enroll Pic

THE MIT XPRO LEARNING EXPERIENCE

  • Learning technique

    LEARN BY DOING

    Practice processes and methods through simulations, assessments, case studies, and tools.

  • Learning technique

    LEARN FROM OTHERS

    Connect with an international community of professionals while working on projects based on real-world examples.

  • Learning technique

    LEARN ON DEMAND

    Access all of the content online and watch videos on the go.

  • Learning technique

    REFLECT AND APPLY

    Bring your new skills to your organization, through examples from technical work environments and ample prompts for reflection.

  • Learning technique

    DEMONSTRATE YOUR SUCCESS

    Earn a Professional Certificate and 3 Continuing Education Units (CEUs) from MIT.

  • Learning technique

    LEARN FROM THE BEST

    Gain insights from twelve esteemed MIT faculty and instructors from MIT's Computer Science and Artificial Intelligence Lab (CSAIL).

MIT FACULTY & INSTRUCTORS

Antonio Torralba

Antonio Torralba

Delta Electronics Professor of Electrical Engineering and Computer Science and Head of the AI+D faculty in the Electrical Engineering and Computer department, MIT

Daniela Rus

Daniela Rus

Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science; Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Deputy Dean of Research for Schwarzman College of Computing, MIT

Yoon Kim

Yoon Kim

Assistant Professor, Electrical Engineering and Computer Science, MIT

Regina Barzilay

Regina Barzilay

Professor, Department of Electrical Engineering and Computer Science; Faculty Co-Lead, MIT Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic), MIT

Armando Solar-Lezama

Armando Solar-Lezama

Professor, Associate Director and COO of CSAIL, MIT

Cynthia Breazeal

Cynthia Breazeal

Professor Media Arts and Sciences, Media Lab; and Dean for Digital Learning, Open Learning, MIT

Zach Lieberman

Zach Lieberman

Adjunct Associate Professor of Media Arts and Sciences, MIT

Pattie Maes

Pattie Maes

Professor of Media Arts and Sciences, MIT

Asu Ozdaglar

Asu Ozdaglar

MathWorks Professor of Electrical Engineering and Computer Science Department Head, Electrical Engineering and Computer Science & Deputy Dean of Academics, Schwarzman College of Computing, MIT

Wojciech Matusik

Wojciech Matusik

Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT

Dylan Hadfield-Menell

Dylan Hadfield-Menell

Bonnie and Marty (1964) Tenenbaum Career Development Assistant Professor of Electrical Engineering and Computer Science, Massachusetts Institute of Technology

Marzyeh Ghassemi

Marzyeh Ghassemi

Assistant Professor in Electrical Engineering and Computer Science, MIT

Phillip Isola

Phillip Isola

Associate Professor in MIT's Department of Electrical Engineering and Computer Science

THE BEST COMPANIES CONNECT WITH THE BEST MINDS AT MIT

Deepen your team’s career knowledge and expand their abilities with MIT xPRO’s online courses for professionals. Develop customized learning for your team with bespoke courses and programs on your schedule. Set a standard of knowledge and skills, leading to effective communication among employees and consistency across the enterprise.

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