BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
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 Phoenix TS Training 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
BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
Phoenix TS 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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