KDDC 2EN08 - Generative IA

In this module, you will gain a comprehensive overview of the world of generative AI. We will start by exploring the fundamental concepts of AI and generative AI, clarifying what they are and how they differ. You will learn about the wide range of possibilities that generative AI offers, as well as its limitations, to understand both its potential and its boundaries.

We will then delve into the technical aspects, explaining how generative AI systems are created, but from a non-technical point of view. No prior knowledge of mathematics or computer science is required. Practical application will be a key focus, as you will learn how to effectively use generative AI tools in various scenarios. To build your confidence, there will be fun, non-technical practical exercises designed to reinforce your understanding and skills.

Furthermore, we will address critical ethical considerations, such as the presence of biases in AI systems, their truthfulness, safety, and overall reliability. These discussions will help you develop a nuanced understanding of the ethical landscape surrounding generative AI.

Finally, we will look at the broader picture by discussing the potential economic impact of generative AI. You will gain insights into how these technologies might transform industries, influence job markets, and shape the future economy.

To enrich your learning experience, we will host prestigious guest speakers, such as the VP of Southern Europe at Meta, who will cover neighboring topics and provide valuable industry insights. This module aims to equip you with both theoretical knowledge and practical skills, preparing you to navigate and contribute to the evolving field of generative AI.

No specific prerequisites are required, other than an interest in generative AI. This is not a technical class, so you need not worry if you are not fond of mathematics.

The class will alternate between live lectures with question-and-answer sessions, guest lectures, and discussions about the homework exercises.

Easy, non-technical, practical homework will be given between sessions and graded. The primary criterion for passing is the completion of the exercises, regardless of correctness.

Depending on timing, the final session might include live presentations and debating.

Between sessions, 1 to 2 hours should be devoted to doing the homework.