Creating Advanced AI Applications with Python, APIs, and GitHub Models
1h 17mAdvanced2025-03-06
Authors
Jonathan Fernandes
Consultant focusing on data science, AI, and big data
Course details
GitHub Models lets you build AI features and products that integrate with third-party APIs. In this course, instructor Jonathan Fernandes shows you how to create an AI application using advanced large language model (LLM) tooling and GitHub Models. Experiment with LLM tooling such as function calling to determine the best LLM for the task, and then start designing and building your own prototype. Test out your new skills along the way in the hands-on coding challenges at the end of each section. By the end of this course, you’ll be equipped with the skills you need to create, test, validate, and deploy an AI-powered app that works effectively with a third-party API.
Learning objectives
Subdivide the problem into smaller pieces.
Choose the right large language model (LLM) for the API-specific task.
Develop a working AI prototype that works with a third-party API.
Demonstrate the AI app, then test and deploy it.
Learning objectives
Subdivide the problem into smaller pieces.
Choose the right large language model (LLM) for the API-specific task.
Develop a working AI prototype that works with a third-party API.
Demonstrate the AI app, then test and deploy it.
Skills covered
Github ModelsOpenAI APIGitHubAPIsOpenAIProgramming FoundationsArtificial Intelligence FoundationsPythonArtificial Intelligence (AI)Programming LanguagesOpen SourceSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Building advanced AI prototypes
1. Using GitHub Models
- 02 - What is Github Models
- 03 - Comparing and selecting a large language model (LLM)
- 04 - The finished product
2. Create the AI Prototype
- 05 - Using GitHub Codespaces
- 06 - Using ExchangeRate-API.com
- 07 - Challenge - Get exchange rate
- 08 - Solution - Get exchange rate
- 09 - Challenge - Choose an LLM supporting multiple languages
- 10 - Solution - Choose an LLM supporting multiple languages
- 11 - Challenge - Create an app layout
- 12 - Solution - Create an app layout
- 13 - Challenge - LLM API call
- 14 - Solution - LLM API call
- 15 - Function calling - Add function calling code
- 16 - Challenge - Function calling
- 17 - Solution - Function calling
- 18 - Challenge - Using tools when required
- 19 - Solution - Using tools when required
- 20 - Deploy the app to production
- 21 - Working with LangSmith
Conclusion
- 22 - Go further with prototyping AI models