[NEW] 2026: Quantization for Gen-AI

In today's rapidly evolving technological landscape, Large Language Models (LLMs) have emerged as a cornerstone of generative AI, capable of revolutionizing industries from content creation to customer service. This comprehensive course is designed to equip you with the essential knowledge and skills to master LLMs and harness their full potential.

Course Objectives

• Gain a deep understanding of the foundational concepts and principles of generative AI and LLMs.

• Explore the intricacies of LLM configuration parameters and their impact on performance.

• Differentiate between stateless and stateful LLMs and their applications.

• Understand the distinction between base LLMs and instruction-tuned LLMs.

• Delve into the economics of model training, including cost considerations and the insights from the Kalpan Paper.

• Explore the groundbreaking research presented in the Chinchilla Paper and its implications for LLM development.

• Master the art of quantization to optimize model size and efficiency.

• Differentiate between Post-Training Quantization (PQT) and Quantization-Aware Training (QAT) techniques.

• Explore the landscape of quantization packages and tools available.

• Learn the practical process of quantizing LLMs to enhance performance and reduce computational requirements.

Why Choose This Course?

• Comprehensive Coverage: Our course provides a thorough understanding of LLMs, from foundational concepts to advanced techniques.

• Hands-On Learning: Engage in practical exercises and projects to apply your knowledge and build real-world applications.

• Expert Guidance: Benefit from the expertise of our experienced instructors who will guide you through the learning process.

• Up-to-Date Content: Stay informed with the latest advancements in generative AI and LLM technology.

Enroll today and embark on a journey to become a master of generative AI and LLMs!