Essentials of LLMs and Generative AI

Mode

Offline / Online  / Weekend

Duration

6 Hours

Who Should Enroll

This course is designed for working professionals, college students, data scientists, and AI enthusiasts who want to understand the fundamentals of large language models (LLMs) and generative AI.

Prerequisites

No prior knowledge is needed. Basic understanding of programming and an interest in artificial intelligence are beneficial.

Program Objectives

The objective of this course is to provide a thorough introduction to LLMs and generative AI, covering both theoretical and practical aspects. Participants will explore the basics of LLMs and generative AI, core concepts such as transformers and attention mechanisms, and practical applications including NLP use cases and chatbots. The course will also delve into the fundamentals of generative AI, including GANs and image generation, as well as training, fine-tuning techniques, and ethical considerations. Participants will engage in hands-on exercises to apply their learning.

Learning Objectives

• Understand the historical evolution and basics of LLMs and generative AI.
• Learn core concepts such as transformers, attention mechanisms, and text processing.
• Explore practical applications including NLP use cases, chatbots, and text generation.
• Compare GANs with LLMs and understand image generation and other generative models.
• Gain knowledge of data preparation, training, and fine-tuning techniques.
• Learn about tools and frameworks for building and deploying applications.
• Discuss ethical considerations including bias, fairness, and responsible AI use.
• Explore future trends and emerging technologies in generative AI.

Key Topics

• Introduction to LLMs and Generative AI: Overview of the basics and historical evolution of these technologies.
• Core Concepts: Transformers, attention mechanisms, and text processing fundamentals.
• Practical Applications: Use cases in natural language processing (NLP), chatbots, and text generation.
• Fundamentals of Generative AI: Comparison of GANs and LLMs, image generation, and other models.
• Training and Fine-Tuning: Techniques for data preparation, training, and fine-tuning models.
• Implementation: Tools and frameworks for building and deploying AI applications.
• Ethical Considerations: Issues related to bias, fairness, and responsible use of AI.
• Future Trends: Emerging technologies and ongoing research innovations.
• Hands-On Exercises: Activities include chatbot creation, case studies, and group discussions.

Faculty and Resources

The course is taught by experienced professionals in the field of AI and generative models. Participants will have access to a range of tools and resources to facilitate hands-on learning and practical application.

Certification

Upon successful completion of the course, participants will receive a Certificate of Participation in Essentials of LLMs and Generative AI.

Register

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