Week 1
GenAI foundations
Understand LLMs, tokens, context windows and responsible use.
LLMsTokens
Detailed learning path
Generative AI Engineer
A 12-week portfolio-first Generative AI path covering prompting, APIs, embeddings, RAG, agents and deployable LLM applications.
Weekly roadmap
What you will learn week by week
Inspired by portfolio-first learning platforms: each module has a clear outcome, practice activity and project artifact.
Week 2
Prompt engineering
Write prompts for reasoning, extraction, summarization and tutoring.
PromptingEvaluation
Week 3
Python API integration
Call LLM APIs and structure inputs/outputs in Python.
PythonAPIs
Week 4
Embeddings and semantic search
Create embeddings and search documents semantically.
EmbeddingsSimilarity
Week 5
Vector databases
Store, retrieve and manage vectorized knowledge.
FAISSChroma
Week 6
RAG fundamentals
Build a PDF chatbot using retrieval augmented generation.
RAGPDF chatbot
Week 7
Evaluation and guardrails
Check hallucination, relevance and response quality.
EvalGuardrails
Week 8
Agentic AI basics
Create simple tool-using agents and workflows.
AgentsTools
Week 9
Multi-step AI workflows
Build workflows for research, career guidance or academic support.
WorkflowsAutomation
Week 10
Deployment
Deploy a GenAI app using Streamlit or a lightweight web interface.
StreamlitDeploy
Week 11
Portfolio and interview prep
Convert projects into resume bullets and GitHub proof.
PortfolioInterview
Week 12
Capstone demo week
Present a production-style GenAI application.
CapstoneDemo
Capstone project
AI Research Assistant
Build a RAG-based assistant that allows users to upload notes or PDFs and ask questions with cited responses.
PythonLangChainVector DBLLM