Clear execution count and outputs in module 1 notebook for a cleaner presentation, enhancing readability and organization.

01-course/module-01-foundations/README.md

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+# Module 1: Foundations
+
+## Course Introduction & Environment Setup
+
+This foundational module introduces you to prompt engineering concepts and gets your development environment configured for hands-on learning.
+
+### Learning Objectives
+By completing this module, you will be able to:
+- ✅ Set up a working development environment with AI assistant access
+- ✅ Identify and apply the four core elements of effective prompts
+- ✅ Write basic prompts for reviewing code
+- ✅ Iterate and refine prompts based on output quality
+
+### Getting Started
+
+**First time here?** 
+- If you haven't set up your development environment yet, follow the [Quick Setup guide](../../README.md#-quick-setup) in the main README first
+- **New to Jupyter notebooks?** Read [About Jupyter Notebooks](../../README.md#-about-jupyter-notebooks) to understand how notebooks work and where code executes
+
+**Ready to start?**
+1. **Open the tutorial notebook**: Click on [module1.ipynb](./module1.ipynb) to start the interactive tutorial
+2. **Install dependencies**: Run the "Install Required Dependencies" cell in the notebook
+3. **Follow the notebook**: Work through each cell sequentially - the notebook will guide you through setup and exercises
+4. **Complete exercises**: Practice the hands-on activities as you go
+
+### Module Contents
+- **[module1.ipynb](./module1.ipynb)** - Complete module 1 tutorial notebook
+
+### Time Required
+Approximately 20 minutes
+
+### Prerequisites
+- Python 3.8+ installed
+- IDE with notebook support (VS Code or Cursor recommended)
+- API access to GitHub Copilot, CircuIT, or OpenAI
+
+### Next Steps
+After completing this module:
+1. Review and refine your solutions to the exercises in this module
+2. Continue to [Module 2: Core Prompting Techniques](../module-02-fundamentals/)

01-course/module-02-fundamentals/README.md

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+# Module 2: Fundamentals
+
+## Core Prompt Engineering Techniques
+
+This module covers the essential prompt engineering techniques that form the foundation of effective AI assistant interaction for software development.
+
+### Learning Objectives
+By completing this module, you will be able to:
+
+- ✅ Apply eight core prompt engineering techniques to real coding scenarios
+- ✅ Write clear instructions with specific constraints and requirements
+- ✅ Use role prompting to transform AI into specialized domain experts
+- ✅ Organize complex inputs using XML delimiters and structured formatting
+- ✅ Teach AI your preferred styles using few-shot examples
+- ✅ Implement chain-of-thought reasoning for systematic problem-solving
+- ✅ Ground AI responses in reference texts with proper citations
+- ✅ Break complex tasks into sequential workflows using prompt chaining
+- ✅ Create evaluation rubrics and self-critique loops with LLM-as-Judge
+- ✅ Separate reasoning from clean final outputs using inner monologue
+
+### Getting Started
+
+**First time here?** If you haven't set up your development environment yet, follow the [Quick Setup guide](../../README.md#-quick-setup) in the main README first.
+
+**Ready to start?**
+1. **Open the tutorial notebook**: Click on [module2.ipynb](./module2.ipynb) to start the interactive tutorial
+2. **Install dependencies**: Run the "Install Required Dependencies" cell in the notebook
+3. **Follow the notebook**: Work through each cell sequentially - the notebook will guide you through setup and exercises
+4. **Complete exercises**: Practice the hands-on activities as you go
+
+### Module Contents
+- **[module2.ipynb](./module2.ipynb)** - Complete module 2 tutorial notebook
+
+### Time Required
+Approximately 90-120 minutes (1.5-2 hours)
+
+**Time Breakdown:**
+- Setup and introduction: ~10 minutes
+- 8 core tactics with examples: ~70 minutes
+- Hands-on practice activities: ~20-30 minutes
+- Progress tracking: ~5 minutes
+
+💡 **Tip:** You can complete this module in one session or break it into multiple shorter sessions. Each tactic is self-contained, making it easy to pause and resume.
+
+### Prerequisites
+- Python 3.8+ installed
+- IDE with notebook support (VS Code or Cursor recommended)
+- API access to GitHub Copilot, CircuIT, or OpenAI
+
+### Next Steps
+After completing this module:
+1. Review and refine your solutions to the exercises in this module 
+2. Continue to [Module 3: Application in Software Engineering](../module-03-applications/)