LLM Fine-Tuning Mastery: Optimize AI Models Like a Pro
Focused View
1:07:01
1 - What is Gen AI.mp4
05:58
2 - What are LLMs.mp4
06:47
3 - Decision Making Build Purchase or Enhance.mp4
06:47
4 - Introduction to Zeroshot Classification.mp4
06:47
5 - Demonstrating a Proof of Concept.mp4
06:47
6 - Essentials of Training and Finetuning.mp4
06:47
7 - Training and Finetuning.mp4
06:47
8 - Supervised Finetuning vs Parameter Efficient Finetunin.mp4
06:47
9 - Approaches to Finetuning.mp4
06:47
10 - Reinforcement learning from human feedback.mp4
06:47
More details
Course Overview
Master cutting-edge techniques to fine-tune and adapt large language models for specialized tasks, from zero-shot classification to RLHF implementation.
What You'll Learn
- Core concepts of generative AI and LLM architectures
- Practical fine-tuning methods including supervised and parameter-efficient approaches
- How to implement reinforcement learning from human feedback (RLHF)
Who This Is For
- AI engineers looking to specialize in LLM optimization
- Data scientists transitioning to generative AI projects
- Tech leads evaluating build-vs-buy decisions for LLMs
Key Benefits
- 10 focused lessons covering the complete fine-tuning pipeline
- Real-world implementation strategies for production environments
- 1+ hour of concentrated, practical instruction
Curriculum Highlights
- LLM Fundamentals & Decision Frameworks
- Core Fine-Tuning Techniques
- Advanced Adaptation Methods
Focused display
- language english
- Training sessions 10
- duration 1:07:01
- Release Date 2025/04/19
