This repository documents my learning journey in Generative AI and Large Language Models (LLMs). It includes notes, experiments, and mini-projects as I explore the fundamentals, implement practical applications, and build hands-on projects using modern AI tools.
The goal is to understand Generative AI concepts, practice real-world examples, and build projects that can be showcased in my portfolio and resume.
- Fundamentals of Generative AI and LLMs
- Prompt Engineering and effective LLM interactions
- Building LLM-powered applications using LangChain
- Text generation, summarization, and question-answering
- Integrating LLMs with external data and APIs
- Deploying simple GenAI applications
- Programming Languages: Python
- AI & ML Tools: Generative AI, LLMs, LangChain
- APIs & Platforms: OpenAI, Hugging Face (as applicable)
- Development Tools: Jupyter Notebook, VS Code
Generative-AI-Learning/
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├── Notebooks/ # Jupyter notebooks for experiments and tutorials
├── Projects/ # Mini-projects built using LLMs and LangChain
├── Notes/ # Markdown notes, cheat sheets, and learning materials
├── Data/ # Sample datasets for experimentation
└── README.md # This file
- Track my learning progress in Generative AI
- Showcase hands-on projects using LLMs and LangChain
- Create a portfolio-ready repository for job applications and resume
🟢 Ongoing – actively adding new notebooks, projects, and experiments.