Capstone Project

Apply everything you’ve learned to solve a real-world problem using AI, ML, and Generative AI tools.

Objective

The Capstone Project is the final step in your AI/ML learning journey. It’s your chance to:

• Combine theory, tools, and techniques from all modules
• Solve a real-world problem or build an innovative product
• Create a portfolio-ready project to showcase to employers, clients, or investors

Key Skills You’ll Apply

• Python Programming
• Machine Learning Models
• Deep Learning with TensorFlow/PyTorch
• Data Analysis & EDA
• NLP with Hugging Face
• Generative AI Tools (ChatGPT, DALL·E, LangChain)
• Vector Databases (FAISS, ChromaDB)
• Web App Development (Streamlit, Flask)

Capstone Project Ideas (Choose One or Customize)

AI-Powered Resume Assistant

Build a chatbot that creates and reviews resumes using OpenAI & LangChain.

• Input: User’s job title & experience
• Output: Tailored resume in PDF + interview tips

GenAI Learning Assistant

Create a personal tutor using Hugging Face models & LangChain memory.

• Input: PDF textbooks or notes
• Output: Summaries, quizzes, explanations

E-commerce AI Assistant

Develop a chatbot that helps users find products, compare prices, and generate product reviews.

• Integrate: Web scraping, GPT, FAISS for memory

AI Startup Idea Generator

• Tool that suggests startup ideas, writes pitch decks, and drafts investor emails using GenAI.

Medical Report Summarizer

• Upload complex health reports or prescriptions → get AI-generated simple explanations.

Capstone Workflow

Problem Statement: Clearly define the problem you’re solving.

Dataset Collection & Preprocessing: Use Kaggle, APIs, or upload your own.

Exploratory Data Analysis (EDA): Use Pandas, Matplotlib, Seaborn.

Model Selection & Training: Choose traditional ML, DL, or LLMs based on problem type.

Integrate GenAI (Optional): Use OpenAI/Hugging Face for chat, summarization, generation.

Deploy as Web App: Use Streamlit or Flask for demo.

Documentation & GitHub Repo: Write clean README, instructions, and upload your code.

Final Deliverables

• Source code (Python files, notebooks)
• Project report with problem, approach, results
• Web app demo (Streamlit or Flask)
• Project screenshots
• Optional: 2-minute video pitch/demo
• GitHub/Portfolio link

Learning Outcomes

After completing your capstone, you’ll be able to:

• Design, build, and deploy end-to-end AI projects
• Work confidently with real-world datasets and LLMs
• Solve practical problems using ML & GenAI
• Build a compelling portfolio to boost your career
• Pitch your ideas to employers or startup incubators