GenAI Interview Kit

It covers the topics below thoroughly:-

Generative AI Fundamentals:
Introduces generative AI concepts, LLM architectures, transformer models, prompt engineering, and fine tuning techniques.

Large Language Models (LLMs):
Explains tokenization, embeddings, context windows, sampling parameters, hallucination challenges, and model evaluation methods.

Prompt Engineering:
Covers zero shot, few shot, chain of thought, ReAct, role based prompting, and optimization strategies for effective outputs.

Retrieval Augmented Generation (RAG):
Focuses on document processing, chunking, vector databases, similarity and hybrid search, RAG design, and performance tuning.

Agentic AI & Multi Agent Systems:
Explores AI agents, tool/function calling, autonomous workflows, multi agent collaboration, memory management, and LangGraph pipelines.

GenAI Application Development:
Teaches building applications with LangChain, LangGraph, OpenAI APIs, LlamaIndex, vector databases, Streamlit, and FastAPI.

AI Solution Architecture:
Covers enterprise AI architecture, scalable RAG solutions, cost optimization, governance, responsible AI, and monitoring practices.

Project1: Enterprise Document Q&A Chatbot:
Builds a RAG powered chatbot for document search, semantic retrieval, and source citation using Python, LangChain, and ChromaDB.

Project2: AI Resume Screening Assistant:
Automates resume parsing, candidate ranking, job matching, and skill gap analysis for recruiters.

Project3: Customer Support AI Assistant:
Delivers AI powered support with FAQ automation, sentiment analysis, and ticket summarization to reduce workload.

Project4: Financial Research Copilot:
Provides financial report summarization, risk analysis, market insights, and AI driven research assistance.

Scenario-Based & Architectural Thinking:
Covered real-world scenario based questions and provided architecture level solutions using GenAI.