Course Description
This course offers a comprehensive introduction to AI development with a primary focus on integrating OpenAI functionalities and tools. Designed for developers already familiar with foundational web technologies, this curriculum dives deep into leveraging OpenAI’s capabilities to build AI-powered applications.
Audience Profile
The audience for this course includes software developers and data scientists who need to use large language models for generative AI.
Challenge Based Projects
The last 2 days of the class students can participate in one of two hands-on projects in an isolated Azure environment (included with the class) to give students practical immersive experience.
Learning Styles
- Presentation
- Hands-on labs
- Challenge based skills.
About this course
Prerequisites
- Visual Studio Code
- Python for Visual Code Studio
- This guide walks you through installing a Python interpreter and the extension needed for using VSCode for Python development.
- Note: Please use version 3.10 of Python. There are issues with existing libraries.
- Upgrade pip to the latest version
- If you are seeing this error “ERROR: Could not build wheels for hnswlib, which is required to install pyproject.toml-based projects” then use the following link as a fix.
- .Net 6 LTS
- Git installed
- Postman
- NodeJS 18+
- Microsoft C++ Build Tools
Course Modules
Module 1: Introduction to OpenAI and Large Language Models
- Provisioning Azure OpenAI Resources
- Creating an Azure OpenAI resource
- Create deployment models
- Embeddings
- Chat
- ChatCompletion
- Test the models in the Playground
- Model Settings and Prompt Engineering
- Temperature, Max Tokens, Engine, Stop Sequence
- Prompt Structure:
- System, User and AI Prompts
- Understanding API keys and endpoints
- Using the API in in Postman & cURL
Module 2: Understanding Large Language Models
- What are large language models (e.g., GPT-3) and their applications?
- Hands-on exploration of GPT-3's capabilities
- Building with Large Language Models
Module 3: Introduction into Azure OpenAI SDK’s
- Azure OpenAI SDKs provide streamlined access to OpenAI's AI models in Azure.
- Support for popular programming languages, making it accessible to a wide range of developers.
- Examples like JavaScript embedded demo show how to embed AI features in web applications.
- Comprehensive tools and demos available for .NET (C#) developers, similar to Python support.
- Module 4: Using the JavaScript SDK with ReactJS
Module 4: Building a ReactJS application with Azure OpenAI
- Integration of Azure OpenAI JavaScript SDK is essential for interaction with OpenAI models.
- Design a user-friendly interface and use React's component-based architecture for user interactions with AI.
Module 5: Azure Integration and Advanced Topics
- Integrating OpenAI into Azure
- Overview of Azure's AI and machine learning services
- How to use Azure Functions and Logic Apps for OpenAI integration
Module 6: Advanced OpenAI Concepts
- Building Advanced OpenAI Applications
Module 7: Deployment, Best Practices, and Use Cases
Module 8: Deployment Strategies
- Choosing the right deployment methods for your OpenAI applications (e.g., Containers, Functions, VMs)
- Scaling and load balancing
- Security, Monitoring, and Best Practices
- Securing OpenAI applications on Azure
- Monitoring, troubleshooting, and best practices
Module 9: Real-World Use Cases and Q&A
- Explore real-world use cases of OpenAI in Azure and have a Q&A session
Team based project:
- Project: AI-Powered Knowledge Mining
Duration
5 Days