This course provides a comprehensive introduction to Generative Artificial Intelligence (AI), suitable for students of all levels and backgrounds, with no prior programming experience required. Students will explore the fascinating world of generative AI, delving into its history, current applications, and underlying technologies.
We will begin with an overview of what generative AI is, tracing its development from early concepts to modern-day innovations. Students will learn about the various applications of generative AI, including content creation, art, music, and more. A significant focus will be on the ethical implications of generative AI, discussing issues of bias, fairness, and the importance of inclusion and diversity in AI development.
Under the hood, we'll uncover the foundational technologies behind generative AI, such as machine learning, neural networks, natural language processing (NLP), speech synthesis, and computer vision. Students will gain insights into how these technologies work and are applied in generative AI systems.
Hands-on labs will allow students to experiment with popular generative AI platforms and explore prompt engineering techniques to interact with these systems effectively. Additionally, students will dip their toes into building generative AI-powered applications using Python and established libraries, providing a practical understanding of how generative AI can be implemented and utilized.
Anticipated Credit Equivalencies:
4 - Computer Science: Introduction to Generative Artificial Intelligence
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Academic Details
Computer science, generative AI