Evolution of Generative AI: From Theory to Revolution
Explore the fascinating journey of AI development, from early concepts to modern generative models, in this comprehensive overview.
Explore the fascinating journey of AI development, from early concepts to modern generative models, in this comprehensive overview.
This engaging course traces the evolution of artificial intelligence from its theoretical foundations to today's powerful generative models. Students explore key technological breakthroughs, fundamental shifts in AI development, and the emergence of transformative technologies like self-supervised learning. The curriculum covers historical milestones, critical developments in deep learning, and the revolutionary impact of transformer architectures. Through expert insights and practical examples, learners gain a deep understanding of how AI has evolved and where it's heading.
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What you'll learn
Understand the evolution of AI from early concepts to modern systems
Identify key breakthroughs in generative AI development
Grasp fundamental differences between traditional and generative AI
Explore transformer architecture and self-supervised learning
Analyze the impact of scaling in AI development
Understand current AI capabilities and limitations
Skills you'll gain
This course includes:
60 Minutes PreRecorded video
2 assignments
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FullTime access
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There are 4 modules in this course
This comprehensive course examines the historical development and current state of generative AI through four detailed modules. Students learn about the evolution of AI from its early concepts to modern applications, with focus on breakthrough technologies and transformative developments. The curriculum covers key topics including the emergence of deep learning, the impact of transformer architectures, self-supervised learning, and future trends in AI development. Special emphasis is placed on understanding the technological advances that enabled current AI capabilities.
Course and Instructor Introduction
Module 1 · 11 Minutes to complete
Where Did "AI" Come From?
Module 2 · 20 Minutes to complete
What's So Different About Generative AI?
Module 3 · 19 Minutes to complete
Gen AI Today and Tomorrow
Module 4 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Chief Data Scientist and Interim Director at Vanderbilt University
Dr. Jesse Spencer-Smith is the Chief Data Scientist and Interim Director of the Data Science Institute at Vanderbilt University, where he also serves as a Professor of the Practice of Computer Science. He leads a team of data scientists and postdoctoral fellows, collaborating with researchers across the university and industry partners while teaching graduate courses on artificial intelligence. Dr. Spencer-Smith holds a PhD in Cognitive Psychology and Cognitive Science from Indiana University and a BS in Computer Science from the University of Florida. His previous experience includes serving as Director of Data Science at HCA Healthcare, where he established the company's first data science team, and as an Assistant Professor of Psychology in Quantitative Methods at the University of Illinois Urbana-Champaign. He has published extensively on AI applications across various fields and is known for his workshops and speaking engagements on AI for diverse audiences. Dr. Spencer-Smith's work emphasizes the importance of data-driven insights in addressing complex problems across sectors.
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