📚 Content

This module focuses on applying programming and AI fundamentals in a practical environment:

1. Python Setup and Environment

  • Install Python on a computer

  • Navigate and work within the development environment

  • Understand Python as a tool for AI development

2. Problem Identification

  • Identify a real-world problem suitable for an AI solution

  • Analyse the root cause of the problem

  • Define clear objectives for the solution

3. Data Preparation

  • Source and collect relevant data

  • Analyse data to gain insights

  • Prepare datasets for machine learning

4. Choosing AI Learning Approaches

  • Explore different learning types:

    • Supervised learning

    • Unsupervised learning

    • Reinforcement learning

  • Select the appropriate approach for the problem

5. Training the AI Model

  • Identify a suitable AI model

  • Train the model using algorithms

  • Evaluate model performance

6. Selecting an ML System

  • Choose an appropriate machine learning system

  • Use AI to predict outcomes without explicit programming

  • Validate and test model performance

7. Running AI Implementation

  • Implement the trained model

  • Test and debug the solution

  • Ensure the solution works in a real-world scenario

🎯 Outcome

By completing this module, learners will be able to develop and implement a basic AI solution using Python, applying end-to-end machine learning processes from problem identification to deployment.

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