Gen AI Fundamentals (en)
The course ‘Gen AI Fundamentals’ is designed to provide a comprehensive understanding of the foundations of generative artificial intelligence (Gen AI). During the course, students will explore a series of key topics, including the basic concepts of Gen AI, design and development techniques, as well as performance evaluation strategies for Gen AI models. Through a combination of instructional labs, each student will be able to work to complete training exercises that will provide practical experience in using the tool for each of the topics covered during the course.
CODE: DSAI202
Category: Artificial Intelligence
Teaching methodology
The course includes educational laboratories in which each student will be able to work in order to complete training exercises that will provide practical experience in using the instrument, for each of the topics covered during the course.
Prerequisites
- Basic knowledge of computer science and programming.
- Understanding of fundamental concepts of artificial intelligence and machine learning.
- Familiarity with programming languages such as Python.
- Understanding of ethics and fairness concepts in artificial intelligence.
- Experience with software application design and development.
The following is an overview of course content:
Key Concepts: This section covers the foundational concepts of Generative Artificial Intelligence (GenAI), providing an overview of its principles and applications.
Prompt Engineering: Participants will learn about the techniques involved in engineering prompts, which are crucial for guiding the output of generative AI models effectively.
Conversations: The course explores interactive conversations with AI models, enabling students to understand how to engage with and guide the responses of generative models in various conversational contexts.
Bias and Fairness: This part addresses the important topics of bias and fairness in AI systems, focusing on how to recognize and mitigate bias in generative AI applications to ensure ethical and equitable outcomes.
Building a GenAI App: Students will be guided through the process of building a simple GenAI application, gaining practical experience in developing and implementing generative models for real-world use cases.
Evaluation: The course concludes with a discussion on evaluating the performance and effectiveness of GenAI models, covering techniques for assessing model outputs and ensuring their quality and reliability.
At the end of the course, participants will be able to:
- Understand fundamental concepts of Generative Artificial Intelligence (Gen AI).
- Learn prompt engineering techniques for Generative AI.
- Conduct interactive conversations with artificial intelligence models.
- Gain insights into bias and fairness concepts in AI.
- Develop the ability to create a simple Gen AI-based application.
- Acquire performance evaluation skills for Gen AI models.
- Take on the challenge of applying learned concepts through a challenging project.
Duration – 1 day
Delivery – in Classroom, On Site, Remote
PC and SW requirements:
- Internet connection
- Web browser, Google Chrome
- Zoom
Language
- Instructor: English
- Workshops: English
- Slides: English
