🤖 AI-Assisted Development Course — Homework Repository

Welcome to the homework repository for the GenAI and Agentic AI for Software Engineering training course! This repository serves as a template for submitting your homework assignments throughout the program.

💡 Pro Tip: Star this repository to easily find it later!

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🚀 Getting Started

Step 1: Fork This Repository

1. Click the Fork button in the top-right corner of this repository page
2. Select your personal GitHub account as the destination
3. Wait for GitHub to create your personal copy of the repository

Step 2: Clone Your Fork

git clone https://github.com/YOUR_USERNAME/ai-assisted-dev-homework.git

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📁 Repository Structure

ai-assisted-dev-homework/
├── 📄 README.md                    # This file
├── 📂 homework-1/                  # Homework 1: Simple API with AI Assistance
│   ├── 📄 README.md               # Your documentation for HW1
│   ├── 📂 src/                    # Your source code
│   ├── 📂 docs/                   # Additional documentation
│   │   └── 📂 screenshots/        # Screenshots demonstrating AI usage
│   └── 📂 demo/                   # Demo files and run scripts
├── 📂 homework-2/                  # Homework 2: Enhanced App with Tests
├── 📂 homework-3/                  # Homework 3: App from Specification
├── 📂 homework-4/                  # Homework 4: Multi-Agent System
├── 📂 homework-5/                  # Homework 5: MCP Server Configuration
└── 📂 homework-6/                  # Homework 6: Capstone Project

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📤 How to Submit Your Homework

1️⃣ Create a Branch for Each Assignment

# For homework 1
git checkout -b homework-1-submission

# Work on your assignment...

git add .
git commit -m "Complete homework 1"
git push origin homework-1-submission

2️⃣ Create a Pull Request

Pull request quality: Do not submit a bare or one-line PR. Prepare a detailed pull request with a full description of what you implemented, how you used AI, how reviewers can run and verify your work, and screenshots (or other demos) where the homework asks for evidence. Homework submitted without a proper PR description and the expected visual documentation will be rejected. Treat the PR body as the primary submission narrative—link to README.md / HOWTORUN.md in the repo, but the PR itself must still stand on its own.

1. Go to your forked repository on GitHub. Do not create pull requests into original repository
2. Click "Compare & pull request" or go to Pull requests → New pull request
3. Set the base repository to the your personal repository
4. Set the base branch to main
5. Set the compare branch to your homework-X-submission branch
6. Fill in the PR template with a thorough write-up, including:
   • ✅ Summary of what you implemented (enough detail for someone unfamiliar with your branch)
   • 🛠️ AI tools used (prompts, workflow, what you verified yourself)
   • ⚠️ Challenges encountered and how you addressed them
   • 📸 Screenshots showing the running solution and, where required, AI-assisted work—embed key images in the PR. Also add them to docs/screenshots/

📌 Home Work without detailed description and screenshots in PR will not be accepted.

3️⃣ Assign the Instructor for Review

1. In the Pull Request, click "Reviewers" on the right sidebar
2. Search for and add the instructor's GitHub username Alexey-Popov
3. Optionally add labels like homework-1, ready-for-review

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📋 Submission Requirements

Each homework submission MUST include a merge-ready pull request on your fork that matches the expectations under Create a Pull Request (detailed description, how to verify, and screenshots or demos as required). Insufficient PR descriptions are grounds for rejection, even if the code is present in the branch.

Each homework submission MUST also include in the repository:

📝 Required Documentation

Item	Description
README.md	Clear explanation of your solution, approach, and AI tools used and author
HOWTORUN.md	Step-by-step guide to run your application

📸 Screenshots (Highly Expected)

Include screenshots demonstrating:

• 🤖 AI tool interactions (prompts and responses)
• ✅ Your application running successfully
• 🧪 Test results (if applicable)
• 💡 Any interesting AI suggestions or corrections

📁 Place screenshots in the docs/screenshots/ folder within each homework directory.

🎬 Provide runnable demo scripts where applicable.

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▶️ How to Run Applications

Each homework folder should contain clear instructions.

🔐 Environment Setup should be detailed to run the application.

Add 🧪 Testing guide.

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📊 Grading Criteria

Your submissions will be evaluated on:

Criteria	Weight	Description
⚙️ Functionality	30%	Does the code work as specified?
📝 AI Usage Documentation	25%	Clear documentation of how AI tools were used
💻 Code Quality	20%	Clean, readable, well-structured code
📚 Documentation	15%	README, comments, and explanations
🎬 Demo & Screenshots	10%	Visual evidence of working solution and AI interaction

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🆘 Getting Help

Contact the 📚instructor.

Collaborate with 👥 classmates (but submit individual work).

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🌟 Good luck with your assignments!