Mastering Genai - Fine-Tune & Adapt Llms Effectively

What you'll learn
Understand and describe the architecture of Generative AI models like GPT and BERT.
Apply fine-tuning methods to adapt LLMs to specific tasks and industries.
Evaluate and optimize LLM performance through advanced techniques
Implement ethical guidelines and best practices in the deployment of GenAI models
Requirements
Basic understanding of AI concepts and terminology; no advanced technical skills required.
Familiarity with Python programming to follow along with coding demos and exercises.
Description
Explore the cutting-edge field of Generative AI with our course, 'Mastering GenAI: Fine-Tune & Adapt LLMs Effectively.' Designed for professionals and enthusiasts alike, this course offers a deep dive into the mechanisms of large language models such as GPT and BERT. You'll learn how to fine-tune these models to meet specific requirements, ensuring they perform optimally across various industries.Through a mix of theoretical insights and practical exercises, participants will explore different fine-tuning techniques including supervised, unsupervised, and reinforcement learning methods. The course will also address the critical aspects of model optimization, such as hyperparameter tuning and avoiding overfitting, to enhance both efficiency and accuracy.A significant focus will be on the ethical deployment of these technologies. You'll learn to navigate the complexities of AI ethics, ensuring your AI solutions are fair and equitable. This course will prepare you to effectively adapt and deploy AI models, making you a valuable asset in any tech-driven industry.By the end of this course, participants will not only understand the theoretical underpinnings of generative AI but also be proficient in implementing and optimizing these models in a practical, ethical, and efficient manner. Whether you're looking to innovate within your organization, kickstart a career in AI, or academically explore AI technologies, this course will serve as a vital stepping stone to achieving those goals.
Overview
Section 1: Introduction
Lecture 1 What is Gen AI ?
Lecture 2 What are LLMs ?
Section 2: Real-world Large Language Models
Lecture 3 Decision Making: Build, Purchase, or Enhance
Lecture 4 Introduction to Zero-shot Classification
Lecture 5 Demonstrating a Proof of Concept
Lecture 6 Essentials of Training and Fine-tuning
Section 3: Fine-tuning Techniques for LLMs
Lecture 7 Training and Fine-tuning
Lecture 8 Supervised Fine-tuning vs. Parameter Efficient Fine-tunin
Lecture 9 Approaches to Fine-tuning
Lecture 10 Reinforcement learning from human feedback
This course is ideal for AI enthusiasts, data scientists, and developers interested in extending their expertise into the realm of fine-tuning and adapting large language models,Suitable for IT professionals looking to leverage GenAI for improving business processes and creating innovative solutions.,Perfect for academic researchers and students in computer science who want practical experience with state-of-the-art AI technologies.,Security architects and engineers who aim to understand the cybersecurity implications of deploying generative AI models in their operations.

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