AI BootCamp

Fast-track your AI career with an intensive 3-month bootcamp designed for advanced learners. Refresh Machine Learning & Deep Learning fundamentals, master Generative and Agentic AI, and build real-world solutions with expert mentorship and focused doubt-clearing.

Apply Now Back to Course Overview

What You'll Get

Course Overview

Artificial Intelligence

Generative AI

Agentic AI

ML & DL Recap

Mock Interview Preparation

Profile Enhancement

Topic Wise Assessment

Real World Use Cases

What Will You Learn?

Refresh and solidify your ML & DL fundamentals.
Learn to create Agentic AI and Multi Agent systems from scratch.
Work on 2 real-world, industry-aligned use cases.
Validate learning through daily & monthly evaluations.
Get weekly live doubt-clearing sessions.
Be interview ready with 3 personalised mock interview sessions.
Get detailed interview question cheat sheet.
Access recorded session videos for flexible learning.
Join an exclusive WhatsApp community for learning & collaboration.

Master interviews with clear project storytelling and strong technical thinking.

Ideal for — Advanced level.

Career Paths: ML Engineer • GenAI Engineer

Course Duration — 3 Months

Curriculum

Course Content

A fast-paced, intensive curriculum from ML foundations to Agentic AI — with real projects and assessments throughout.

Program Highlights

3 Mock Interviews 2 Module-wise Evaluations 4 Real-world Use Cases Final Capstone Project 2 Self-Paced / Group Project Assignments Daily Topic-wise Evaluation

Initial Knowledge Assessment

Module 1

Machine Learning

ML Foundations

Feature Engineering, Outlier Detection, Performance Evaluation, Bias-Variance Tradeoff, Data Imbalance

Supervised Learning

Predictive & Descriptive Analytics, Classification, Regression, Dimensionality Reduction, Regularization, Overfitting & Underfitting

Unsupervised Learning

Clustering, Recommendation Engine

ML Use Case

Data Processing, Data Manipulation, Scikit-Learn Model Family, 1 real-world Classification use case

Module 2

Deep Learning Essentials

Network Basics

Activation Functions, Optimisation Algorithms, ANN

Computer Vision

CNN, CV Applications, Image Pre-processing, CNN Architectures

NLP

RNN, LSTM, GRU, Transformer Architectures, NLP Use cases

DL Use Case

1 real-world NLP use case

Project: NLP / Computer Vision / Machine Learning

Assessment: ML & Deep Learning Technical — A Deep Dive Assessment (MCQ)

Module 3

Generative AI & LLMs

GenAI Foundations

LLM types, Open source vs closed source models

Prompt Engineering

Zero-shot, Few-shot, Chain-of-thought

Open Source Model Hosting

HuggingFace, GPU basics, Quantization, FastAPI, LangChain

GenAI Safety

Responsible AI, Guardrails, Evaluation Strategies

Module 4

RAG Applications

RAG Systems

Introduction to RAG, Data Ingestion from PDF, TXT, Word

Vector Databases & Embeddings

Vector DBs, Embedding Models

Advanced RAG

Pre-retrieval & post-retrieval strategies, Re-ranking, Evaluation

Project: End-to-end RAG solution + Chatbot use case

Assessment: Generative AI & its applications evaluation

Module 5

Agentic AI & Multi-Agent Systems

Foundations

AI Agents, Reflection, Reflexion, ReAct

Agentic Components

Tool calling, Function calling, Memory

Pre-built & Multi-Agent

LangChain Agents (ReAct, MRKL), LangGraph, CrewAI

Agentic AI Use Case

Real-world use case on Agentic AI

Project: Final Capstone Project

Final Capstone Project — Presentation & Evaluation

Mock Interview 2

Mock Interview 3 (At your own pace)

Get Started

Register Your Interest

Fill in your details and we'll reach out with enrollment information, batch schedules, and next steps.

FAQ

Frequently Asked Questions

This course is ideal for students with advanced level of AI knowledge.

This course is a fast-paced course designed for students who have advanced level of AI knowledge. The aim of this course is to do revision-based learning and regular assessments. It's a bootcamp that students can enroll in to prepare for their upcoming interviews.

The Initial Knowledge Assessment is the first round of evaluation conducted by TheAIClan to understand your knowledge levels.

The result of the assessment would be a detailed report containing analysis about your areas of excellence and areas of improvement in your AI journey. It also classifies your knowledge at beginner, intermediate, and advanced levels.

There are three types of evaluation: 1. Daily Topic Wise Assessment (DTWA) 2. Module Completion Assessment (MCA) 3. Mock Interviews.

Yes, Daily Topic Wise Assessment (DTWA) and Module Completion Assessment (MCA) will be MCQ based. MCA will be a detailed 1-hour assessment.

This is an industry-simulating interview — a personalised 1-on-1 session which will have both coding and technical questions. A detailed review would be shared over email on areas of improvement and areas of excellence.

These are assignments given to individuals in the class. They can choose to either work in groups or individually. We can facilitate group creation in the class.