Unleash the power of Generative AI and Large Language Models in just 30 days!

Welcome to a transformative journey into the world of Generative AI and LLMs! Over the next 30 days, we’ll dive deep into cutting-edge topics—from the nuts and bolts of Transformer architectures to building conversational agents and deploying production-ready AI systems.

What you'll get:

• Daily Deep Dives: Each day features a focused topic, real-world projects, and hands-on coding challenges.
• Interactive Notebooks: Detailed Jupyter notebooks with clear explanations, examples, and exercises.
• Practical Projects: From prompt engineering to building recommendation systems, every project is designed to boost your practical skills.
• Community & Collaboration: Share your progress, contribute ideas, and connect with like-minded enthusiasts.

Here's a sneak peek at the daily topics along with their key highlights and deliverables:

Scroll down for full details on each day’s challenge!

This marathon covers a wide spectrum of topics and tools, including:

• Generative AI Fundamentals: From conceptual overviews to practical applications.
• Transformer Models: Deep dives into architecture, self-attention, and real-world use cases.
• Prompt Engineering: Techniques to optimize outputs from your LLMs.
• Fine-Tuning & Evaluation: Adapt models for specific tasks and measure performance with metrics like BLEU, ROUGE, and perplexity.
• LangChain & RAG: Build dynamic systems that combine retrieval with generation.
• Deployment & Monitoring: Transform models into production-grade APIs and monitor their performance.
• Ethics & Security: Address bias, fairness, and ensure robust AI practices.

Tech Stack Highlights:

• Language: Python 🐍
• Frameworks/Libraries: PyTorch, TensorFlow, Hugging Face Transformers, FastAPI, Flask
• Visualization & Data: Matplotlib, Seaborn, NumPy, Pandas
• Interactive Environment: Jupyter Notebook / Google Colab

The repository is organized as follows:

30-Day-GenAI-LLM-Marathon/
├── Day_1/
│   ├── Intro_to_Generative_AI.ipynb
│   └── README.md
├── Day_2/
│   ├── Transformer_Architecture.ipynb
│   └── README.md
├── Day_3/
│   ├── HuggingFace_Essentials.ipynb
│   └── README.md
├── ... (more daily folders)
├── requirements.txt
└── README.md  (this file)

Each day’s folder includes:

• Jupyter Notebooks: Detailed explanations, code examples, and exercises.
• Day-Specific README: Summaries of concepts, tasks, and key takeaways.
• Datasets/Resources: Provided directly or linked for further exploration.

To kick off the marathon:

1. Clone the Repository:

   git clone https://github.com/your-username/30-Day-GenAI-LLM-Marathon.git
   cd 30-Day-GenAI-LLM-Marathon

2. Install Dependencies:

   pip install -r requirements.txt

3. Launch Your Notebook Environment:

   • Open the Jupyter Notebooks in any daily folder using Jupyter Notebook or Google Colab.
   • Run the code, experiment, and learn!

This marathon is all about collaboration and shared learning. You can:

• Contribute: Fork the repository, add your ideas or improvements, and submit pull requests.
• Share Feedback: Use the Issues section to discuss challenges, share insights, or ask for help.
• Spread the Word: If you find this project valuable, give it a star ⭐ and share your progress on social media!

I created this challenge to:

• Demystify Generative AI & LLMs: Provide an accessible, hands-on learning experience.
• Bridge Theory & Practice: Equip you with both the knowledge and skills needed for real-world AI projects.
• Foster Community: Build a collaborative environment where we can all learn from one another.

If you're passionate about AI and eager to explore the next frontier of technology, you're in the right place!

Thank you for joining the 30-Day GenAI & LLM Marathon. Let’s code, learn, and innovate together!

Happy Learning & Coding! 🚀