Fine-Tuning Large Language Models: Maximizing Value and Performance for Custom AI Solution

Training Summary
In this 2-day course, participants will learn how to fine-tune large language models like Chat-GPT to build custom AI solutions tailored to specific use cases and domains. The course will cover the essentials of fine-tuning, including data preparation, model selection, and training best practices. Participants will also learn how to evaluate and optimize fine-tuned models for improved performance, fairness, and safety. The course will provide hands-on experience through guided exercises and real-world examples, highlighting various use cases such as content generation, sentiment analysis, and customer service. By the end of the course, participants will be equipped with the skills and knowledge required to develop high-performing, customized AI solutions that deliver tangible value to their organizations.
  • Strong understanding of AI and machine learning concepts
  • Familiarity with natural language processing (NLP) techniques and tools
  • Experience in Python programming and working knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch)
2 Days/Lecture & Lab
Data scientists, AI/ML engineers, software developers, and professionals interested in developing custom AI applications using large language models like Chat-GPT
Course Topics
  • Introduction to Large Language Models and Fine-Tuning
  • Data Preparation and Model Selection
  • Training and Optimizing Fine-Tuned Models
  • Evaluating Model Performance, Fairness, and Safety
  • Fine-Tuning for Various Use Cases and Domains
  • Capstone Project

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