Azure OpenAI Fundamentals Hackathon
Gain hands-on experience with prompt engineering and machine learning best practices in this 1-day guided hackathon.
This hack is for anyone who wants to gain hands-on experience experimenting with prompt engineering and machine learning best practices, and apply them to generate effective responses from ChatGPT and OpenAI models.
Participants will learn how to:
- Compare OpenAI models and choose the best one for a scenario
- Use prompt engineering techniques on complex tasks
- Manage large amounts of data within token limits, including the use of chunking and chaining techniques
- Grounding models to avoid hallucinations or false information
- Implement embeddings using search retrieval techniques
- Evaluate models for truthfulness and monitor for PII detection in model interactions
About this course
- Prepare your workstation to work with Azure.
- What's possible through Prompt Engineering
- Best practices when using OpenAI text and chat models
- What are the capacities of each Azure OpenAI model?
- How to select the right model for your application
- Why is grounding important and how can you ground a Large Language Model (LLM)?
- What is a token limit? How can you deal with token limits? What are techniques of chunking?
- How do we create ChatGPT-like experiences on Enterprise data? In other words, how do we "ground" powerful LLMs to primarily our own data?
- What are services and tools to identify and evaluate harms and data leakage in LLMs?
What are ways to evaluate truthfulness and reduce hallucinations? What are methods to evaluate a model if you don't have a ground truth dataset for comparison?