Advanced LLM Development with OpenAI Training Course in Bangkok, Thailand

This advanced training course is designed for experienced developers seeking to master the intricacies of building and deploying Large Language Models (LLMs) with OpenAI. Participants will explore advanced prompt engineering, fine-tuning strategies, function calling, and retrieval-augmented generation (RAG). The curriculum emphasizes practical implementation, covering API integration, model evaluation, and deployment best practices for production-grade AI applications. Through a series of structured sessions, learners will gain the skills to build sophisticated, context-aware conversational agents and automated workflows.

Advanced Prompt Engineering and Context Management

• Crafting multi-turn prompts for complex reasoning
• Using system messages and user roles effectively
• Techniques for managing token limits and context windows
• Dynamic prompt templates for variable inputs

Hands-on exercises

Fine-Tuning and Model Customization

• Preparing and formatting datasets for fine-tuning
• Running fine-tuning jobs with OpenAI API
• Evaluating fine-tuned model performance
• Best practices for versioning and iterating models

Hands-on exercises

Function Calling and Tool Integration

• Defining function schemas for API interactions
• Handling function call responses in chat completions
• Building a multi-tool assistant for data retrieval
• Error handling and retry logic in tool use

Hands-on exercises

Retrieval-Augmented Generation (RAG)

• Architecting RAG pipelines with vector databases
• Embedding documents and querying relevant chunks
• Integrating retrieval with OpenAI chat completions
• Optimizing chunk size and overlap for accuracy

Hands-on exercises

Model Evaluation and Iteration

• Defining quality metrics: accuracy, relevance, safety
• Building automated evaluation datasets
• Using human feedback loops for continuous improvement
• Versioning prompts and models for A/B testing

Hands-on exercises

Production Deployment and Scaling

• Setting up API gateways and rate limiting
• Implementing caching strategies for cost efficiency
• Monitoring latency, throughput, and error rates
• Securing API keys and managing access controls

Hands-on exercises

Advanced Use Cases and System Design

• Building multi-agent systems with OpenAI
• Designing conversational AI with memory and state
• Integrating LLMs with existing enterprise systems
• Ethical considerations and bias mitigation

Hands-on exercises