Certified 7-Day AI Bootcamp: AI Apps, RAG, and AI Agents

Learn AI by building projects with Python, LLMs, Streamlit, prompt engineering, RAG, AI Agents, Multi-Agent Workflows

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Build practical AI applications using Python, Streamlit, and Large Language Models.
Understand modern AI concepts including Generative AI, LLMs, tokens, prompts, context windows, and hallucinations.
Write effective prompts using roles, instructions, constraints, examples, and structured output formats.
Create a Prompt Engineering Playground to test, compare, and save reusable prompts.
Build an AI Resume Analyzer that reviews resumes, scores them, and suggests improvements.
Extract text from PDFs and documents for use in AI applications.
Build a PDF Chat Assistant using Retrieval-Augmented Generation, also known as RAG.
Understand embeddings, semantic search, document chunking, and vector databases.
Use ChromaDB as a local vector database for document search and retrieval.
Build an autonomous AI Research Agent that can plan, search, analyze, write, review, and save reports.
Create a multi-agent workflow with Planner, Researcher, Writer, Editor, and QA agents.
Package an AI application with Docker and prepare it for portfolio or deployment.
Apply responsible AI practices including privacy, accuracy, guardrails, and human oversight.
Create portfolio-ready AI projects suitable for GitHub, resumes, interviews, and demos.

No advanced AI, machine learning, or data science background is required.
Basic Python knowledge is helpful, but the course is beginner-friendly and explains the code step by step.
Basic command line or terminal knowledge is helpful for running Python apps and installing packages.
Students should have a computer with internet access.
An OpenAI API key is optional. Students can also use Ollama to run local models where supported.
Basic familiarity with APIs, web apps, or software development is helpful, but not required.
No advanced math is required.
No prior experience with RAG, AI agents, vector databases, Streamlit, ChromaDB, or Docker is required. These topics are introduced from the ground up through hands-on labs.
Most importantly, students should be curious and ready to build practical AI projects step by step.

Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!

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