Course Overview
In this two day, instructor led AI Solutions course in Washington, DC Metro, Tysons Corner, VA, Columbia, MD or Live Online, participants learn how to fine-tune large language models (LLMs) like Chat-GPT to build custom AI solutions tailored to specific use cases and domains. This course covers fine-tuning fundamentals, 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. This course is intended for Data scientists, AI/ML engineers, software developers, and professionals interested in developing custom AI applications using large language models like Chat-GPT. At the completion of this course, participants will be able to:
- Understand the principles and benefits of fine-tuning large language models like Chat-GPT
- Prepare data sets and choose appropriate models for fine-tuning tasks
- Implement best practices for training and optimizing fine-tuned models
- Evaluate model performance, fairness, and safety in custom AI applications
- Apply fine-tuning techniques to create AI solutions for various use cases and domain
Schedule
Currently, there are no public classes scheduled. Please contact a LEXX LIVETraining Consultant to discuss hosting a private class at 301-258-8200.
Prerequisites
All learners are required to have:
- 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)
Course Outline
Introduction to Large Language Models and Fine-Tuning
- Overview of large language models (e.g., GPT-3, Chat-GPT)
- Benefits and challenges of fine-tuning
- Introduction to fine-tuning techniques and tools
Data Preparation and Model Selection
- Principles of data selection and annotation for fine-tuning
- Techniques for data preprocessing and cleaning
- Criteria for selecting base models and architectures
Training and Optimizing Fine-Tuned Models
- Best practices for training and hyperparameter tuning
- Techniques for model optimization and regularization
- Monitoring model convergence and addressing overfitting
Evaluating Model Performance, Fairness, and Safety
- Metrics and techniques for model evaluation
- Identifying and mitigating biases in fine-tuned models
- Ensuring content safety and adherence to ethical guidelines
Fine-Tuning for Various Use Cases and Domains
- Customizing AI solutions for content generation, sentiment analysis, customer service, and more
- Adapting fine-tuning techniques for domain-specific applications
Capstone Project
- Participants will apply the concepts and techniques learned throughout the course to fine-tune a large language model for a custom AI solution addressing a real-world challenge or opportunity
- Presentation and discussion of capstone projects
LEXX Live is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints re-garding registered sponsors may be submitted to the National Registry of CPE Sponsors through its web site: www.nasbaregistry.org
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