AI Reasoning Models in Practice: Building an AI-Powered Coach

This is the repository for the LinkedIn Learning course AI Reasoning Models in Practice: Building an AI-Powered Coach. The full course is available from LinkedIn Learning.

Course Description

AI reasoning models are changing how we interact with AI, providing more structured, logical, and multistep responses compared to traditional GPT models. In this project-based course, learn when and how to use reasoning models as you create an AI-powered personal coach. Instructor Kesha Williams—a leader in enterprise architecture and AI strategy and governance—provides hands-on challenges that allow you to apply reasoning models to decision-making, code understanding, and image-based reasoning while optimizing model efficiency. Whether you’re a developer or data scientist looking to integrate advanced reasoning models into practical solutions—or a technical decision-maker interested in the capabilities and applications of AI reasoning models—this course can help you integrate this exciting technology into real-world AI workflows.

This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace.

Requirements

• Python 3.9+
• An OpenAI API key

Setup

1. Clone this repo (or download the files).
2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate   # macOS/Linux
   venv\Scripts\activate      # Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Set your OpenAI API key or place in .env file:

   export OPENAI_API_KEY="your_api_key"      # macOS/Linux
   setx OPENAI_API_KEY "your_api_key"        # Windows PowerShell

Instructor

Kesha Williams

Award-Winning Tech Innovator and AI/ML Leader