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Driving Innovation with Generative AI
Explore the generative AI landscape and the future of productivity with this 6-week course from MIT xPRO.
Start Date
February 10, 2025
Duration
6 weeks
Price
$2,979
Save 15% this month only with code NEWYEAR25 -- that's over $446 in savings!
GET YOUR COURSE SCHEDULE
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Start Date
February 10, 2025
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Duration
6 weeks
.svg)
Price
$2,979
Save 15% this month only with code NEWYEAR25 -- that's over $446 in savings!
Start Date
February 10, 2025
Duration
6 weeks
Price
$2,979
Save 15% this month only with code NEWYEAR25 -- that's over $446 in savings!
UNLEASH THE POWER OF GENERATIVE AI
Generative AI represents a seismic shift in the way we approach creative tasks. A comprehensive understanding of these technologies enables organizations to leverage the power of the technology to increase productivity, improve customer service, enhance user experiences, develop content, create synthetic data, enable new discoveries, and so much more!
Become an essential part of your organization’s generative AI journey. Develop an essential understanding of generative AI’s key technologies and how they may be used in various applications.
Generative AI is creating cutting-edge solutions that will revolutionize industries and empower businesses to thrive in the digital age. This course will leverage industry case studies, hands-on work with generative AI tools, and the latest thinking from MIT to equip you with the knowledge and skills necessary to navigate the intricate world of generative AI.
TOPICS THAT WILL BE COVERED INCLUDE:
- Generative AI and the AI Landscape
- Generative AI Foundations: Visual Data and Image Outputs
- Generative AI Foundations: Textual Data and Text Outputs
- Other Types of Data and Applications They Enable
- Generative AI for Creativity Expression and Design of Collaborative Agents
- Strategy and Societal Implications of Generative AI (Policy, Ethics, and Human Augmented Work)
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AFTER THIS COURSE, YOU WILL BE ABLE TO
Develop a comprehensive understanding of the fundamentals and distinctions of Generative AI and machine learning such as neural networks and the role of data.
Explore the collaborative efforts and connection between Generative AI and humans, focusing on creative expression and human emotion.
Acquire the skills to analyze and utilize image generative models, including comprehending their key components, inputs, and outputs, and critically assess the significance of latent variables and noise in their operational effectiveness.
Understand Generative AI in coding, design, and chemistry, mastering algorithms for molecular property prediction and code generation, and comprehending the fundamental architectures for molecular design, code creation, and 3D structural design.
Evaluate the evolution, limitations, and future possibilities of Large Language Models (LLMs), tracing their developmental history, understanding current constraints, and exploring potential advancements and applications in various fields.
Recognize the essentials of Pro-Human Generative AI to enhance human decision-making and societal interactions, focusing on addressing biases, best practices in health and societal applications, and aligning AI with developer and user goals through measurement, feedback-driven reinforcement learning, and deployment strategies.
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.
MIT FACULTY
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
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
Assistant Professor, Electrical Engineering and Computer Science, MIT
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
Professor, Associate Director and COO of CSAIL, MIT
Cynthia Breazeal
Professor Media Arts and Sciences, Media Lab; and Dean for Digital Learning, Open Learning, MIT
Zach Lieberman
Adjunct Associate Professor of Media Arts and Sciences, MIT
Pattie Maes
Professor of Media Arts and Sciences, MIT
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
Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT
Dylan Hadfield-Menell
Bonnie and Marty (1964) Tenenbaum Career Development Assistant Professor of Electrical Engineering and Computer Science, Massachusetts Institute of Technology
Marzyeh Ghassemi
Assistant Professor in Electrical Engineering and Computer Science, MIT
Phillip Isola
Associate Professor in MIT's Department of Electrical Engineering and Computer Science
WHAT LEARNERS ARE SAYING
Professionals around the globe have taken this course to better navigate the intricate world of generative AI
This course was a game-changer!
This course was a game-changer! It provided clear, practical insights that helped me unlock AI's potential for creative problem-solving and innovation.
Bedanta Saha
Data Scientist
This course was packed with all aspects of Gen AI
This was my first introduction into Gen AI and this course was packed with all aspects of Gen AI. Learning about machine learning, neural networks, frameworks, modeling, creating custom ChatGPTs and more. It was a lot of work, but worth it. I have completed this course with a better understanding of how AI systems are created through the training data sets, and how to apply these systems in the real world.
Shari Bijaczyk
TS Digital Solution Engagement Lead/Manager
An excellent foray into the world of innovation and AI
This course is an excellent foray into the world of innovation and AI, developing a unique perspective on both potential and risks associated with AI. Overall, this course and the faculty behind it delivered on the promise to help you develop as a more well rounded AI professional.
Devin Hundt
Process Engineer
Learned a lot about different AI tools and their usage
Great course, materials were organized very well. Learned a lot about different AI tools and their usage and also how to design and build Gen AI integrated systems.
Mahnaz Shafii
Manager of Software Development
The MIT professors are excellent and the assignments stretch your brain
This course covered the breadth of how Generative AI works, the challenges of making it work, both technological and ethical. It covers the theory of Natural Language Processing, LLMs, for applicability into various disciplines. The MIT professors are excellent and the assignments stretch your brain.
Amit Rele
Digital Transformation Executive
I cannot emphasize enough the exceptional quality and comprehensive nature of this learning experience
MIT's reputation for academic excellence is clearly reflected in this program's rigorous content and professional delivery. For anyone looking to develop expertise in Generative AI, this course offers an ideal blend of academic depth and practical skill development. It has significantly enhanced my understanding of AI technologies and their applications in today's rapidly evolving technological landscape.
Jason McCormick
Chief Operating Officer
Looking forward to putting the new skills into successful action.
An excellent course with the right balance of ideas, and implementation. Looking forward to putting the new skills into successful action.
Matt Gough
Director of Digital Innovation
RESOURCES
Inside MIT xPRO's Generative AI Online Certificate Course
MIT's Antonio Torralba discusses who this online course is meant for, what you will learn, and why it's different from other AI courses.
Wednesday, January 22, 2025
Overcome the Barriers to Generative AI Adoption in the Workplace
Along with generative AI's rapid evolution comes a host of challenges that many organizations and employees aren’t fully prepared to tackle.
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Exploring the Shift from Traditional to Generative AI
Understanding the differences between traditional and generative AI can help today’s professionals better prepare for the new frontier of generative AI.
THE MIT XPRO LEARNING EXPERIENCE
LEARN BY DOING
LEARN BY DOING
Practice processes and methods through simulations, assessments, and tools including DALL-E, Midjourney, Leonardo, Runway, ChatGPT 4, Gemini, and Claude 3.5 Sonnet
LEARN FROM OTHERS
LEARN FROM OTHERS
Connect with an international community of professionals while working on projects based on real-world examples through discussion forums and weekly live webinars
LEARN ON DEMAND
LEARN ON DEMAND
Access all of the content online and watch videos on the go
REFLECT AND APPLY
REFLECT AND APPLY
Bring your new skills to your organization, through examples from technical work environments and ample prompts for reflection
DEMONSTRATE YOUR SUCCESS
DEMONSTRATE YOUR SUCCESS
Earn a Professional Certificate and 3 Continuing Education Units (CEUs) from MIT
LEARN FROM THE BEST
LEARN FROM THE BEST
Gain insights from twelve esteemed MIT faculty and instructors from MIT's Computer Science and Artificial Intelligence Lab (CSAIL) plus weekly live webinars
JUSTIFY YOUR PROFESSIONAL DEVELOPMENT
