Understanding Neural Networks: The Foundation of AI
AI and machine learning are spurring innovation across industries, governments, and daily life at remarkable speed. This course covers core concepts like neural networks and supervised learning, along with key applications, risks, and policy considerations shaping the future of these technologies.
What you will learn
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Learn the basics about how AI and machine learning works, what it takes to develop these sophisticated algorithms, and where they are going next.
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Examine the ethical and policy concerns related to this quicky evolving technology.
Course content
Introduction to AI
Explore the nature and function of neural networks, the building blocks of AI designed to mimic the human brain. Examine the evolving landscape of generative AI, where machine learning has transitioned from specific dataset applications to the continuous training of foundational models adaptable to various tasks.
Generative AI
Explore the capabilities and constraints of generative AI, unraveling its significance and training process. Journey into the next frontier of AI – multimodal – as it integrates diverse modalities such as sight, sound and touch to craft a more holistic representation of reality.
Ethics and Policy
Examine the ethical considerations surrounding AI and delve into effective strategies for addressing them. Gain insights into pivotal areas where policy intervention is needed.
Your Course Director
Dr. Eugenio Culurciello
Professor of the Weldon School of Biomedical Engineering
Eugenio Culurciello (S'97-M'99) received the Ph.D. degree in Electrical and Computer Engineering in 2004 from the Johns Hopkins University, Baltimore, MD. He is currently a Professor of the Weldon School of Biomedical Engineering at Purdue University, where he directed the ‘e-Lab’ laboratory. His research focus is in general artificial intelligence, deep learning, robotics and 3D understanding, healthcare and life-science applications. Eugenio Culurciello is the recipient of The Presidential Early Career Award for Scientists and Engineers (PECASE), the Distinguished Lecturer of the IEEE (CASS), and is the author of the book "Silicon-on-Sapphire Circuits and Systems, Sensor and Biosensor interfaces" published by McGraw Hill in 2009, and "Biomedical Circuits and System, Integrated Instrumentation" published by Lulu in 2013.