Driving Innovation with Generative AI

Explore the generative AI landscape and the future of productivity with this 6-week course from MIT xPRO coming spring 2024.

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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)

Start Date

Fall 2024

Duration

6 weeks

FORMAT

Online

Description Goes Here

After This program, 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.

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.

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.

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.

Explore the collaborative efforts and connection between Generative AI and humans, focusing on creative expression and human emotion.

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.

MIT FACULTY & INSTRUCTORS

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 ScienceDepartment 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 inElectrical Engineering and Computer Science, MIT

WHO SHOULD ENROLL

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

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

The MIT xPRO Learning Experience

We bring together an innovative pedagogy paired with world-class faculty.

LEARN BY DOING

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

LEARN FROM OTHERS

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

LEARN ON DEMAND

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

REFLECT AND APPLY

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

DEMONSTRATE YOUR SUCCESS

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

LEARN FROM THE BEST

Gain insights from esteemed MIT faculty and industry experts.

Propel Your Career On Your Terms

Technology is accelerating at an unprecedented pace causing disruption across all levels of business. Tomorrow’s leaders must demonstrate technical expertise as well as leadership acumen in order to maintain a technical edge over the competition while driving innovation in an ever-changing environment.

MIT uniquely understands this challenge and how to solve it with decades of experience developing technical professionals. MIT xPRO’s online learning programs leverage vetted content from world-renowned experts to make learning accessible anytime, anywhere. Designed using cutting-edge research in the neuroscience of learning, MIT xPRO programs are application focused, helping professionals build their skills on the job.

Embrace change. Enhance your skill set. Keep learning. MIT xPRO is with you each step of the way.

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