LIVE AI Engineering Bootcamp: Build, Deploy & Scale AI Products

Starts 15th Aug 590+ software engineers enrolled across cohort 1 & 2

From Software Engineer to AI Engineer in 75 Days

Cohort 3 · Starts Saturday, 15th Aug , 2026. A live cohort-based bootcamp that takes you from writing code to shipping production-grade AI systems - RAG, agents, multi-agent orchestration, fine-tuning, and deployment. Taught by practitioners. Built with rigour.

Includes AI Engineering & Data Science Bootcamp 4.0 worth US$345.

11

Weekends


22

Live Sessions


6+

Real Projects

1

Capstone Project


1 Year

Access to LIVE Class Recording


246+

Enrolled Learners

LIVE AI Engineering Bootcamp: Build, Deploy & Scale AI Products
US$660
US$840 after 12th Aug · Save US$180
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In-demand Skills

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Codebasics Promise

We stand by the quality of our content. Not satisfied? No questions asked refund until 17th Aug 2026.

Added Benefit

If you have already taken our paid AI Engineering & DS course(s) or bootcamp, you will pay only the difference (This Bootcamp Price - Money You Paid for AI Engineering & DS course(s) or bootcamp Price)

11

Weekends


22

Live Sessions


6+

Real Projects

1

Capstone Project


1 Year

Access to LIVE Class Recording


246+

Enrolled Learners

What Makes This Bootcamp Different?

  • 100% LIVE, instructor-led sessions every weekend. Real-time interaction, Q&A, and doubt clearing.

  • Covers the FULL AI engineering spectrum, from LLM fundamentals, embeddings & vector databases to RAG, agents, multi-agent systems, fine-tuning, context engineering, cost optimisation, and cloud deployment. This isn’t just an agentic framework course

  • Designed and taught by AI industry experts & engineering leaders with real-world experience building and shipping AI systems at scale

  • Master the complete modern AI stack: Python, FastAPI, LangChain, LangGraph, DSPy, MCP, Qdrant, LangSmith, AWS, Unsloth, Ollama & more

  • Production-first mindset: Cost optimisation, caching, rate limiting, model routing & scaling the engineering challenges that matter in real products

  • LLM Fine-Tuning with LoRA/QLoRA + running models locally with Ollama go beyond API wrappers

  • Context Engineering & MCP (Model Context Protocol), the newest paradigms that top AI teams are adopting right now

  • Guardrails, evaluations, adversarial attacks & compliance - build AI that’s safe for production

  • Capstone project with architectural guidance + live project showdown in front of experts

  • Live interview prep tips with industry AI leaders to prepare you for real AI engineering interviews

  • Integrated soft skills training: AI Product Thinking, Personal Branding, Stakeholder Management, Time Management & Deep Work

  • Practical job assistance: Resume building, LinkedIn optimization, interview preparation, everything you need to land the AI engineer role

Hear It From

Our Happy Learners

Our content is rated 4.9/5 from 24934+ Learners

Overview

What you'll learn in
this Live AI Engineering for Software Engineers Bootcamp

Week-1: AI Foundations & LLM Fundamentals

Python & LLM Basics

  • Session 1 – Kickoff and Fundamentals

    AI Landscape · Python Fundamentals (functions, file manipulation, classes & objects) · APIs & Decorators ·

    Output: Your First LLM-Powered App (Streamlit + Groq)


  • Session 2 – LLMs, Embeddings & Transformer Architecture

    How does an LLM work? · Transformer Architecture · Embeddings & Semantic Similarity · Key Parameters in LLMs

    Output: Embedding & Semantic Similarity in depth Understanding

  • Session 3 – Vector DBs & RAG

    Introduction to VectorDB · Qdrant Hands-on · RAG in Pure Python · Qdrant Advanced Ops

    Output: Your First RAG Pipeline


  • Session 4 – LangChain, Docling & Chunking Strategies

    LangChain Intro · RAG in LangChain · Docling Document Parsing · Hierarchical Chunking

    Output: LangChain RAG Pipeline with Smart Chunking

  • Session 5 – Advanced RAG Techniques & Hands-On

    Vector & Vectorless RAG Architectures · Hybrid RAG · SQL RAG · Graph RAG

    Output: Advanced RAG, Hybrid Search, Reranking


  • Session 6 – Agentic AI Foundations

    What are AI Agents? · Tool Calling & ReAct Loop · Building your first Agent with LangChain · Routing with Semantic Router · Memory in Agents

    Output: Your First Tool-Calling Agent

  • Session 7 – Agent Orchestration & LangGraph

    Introduction to LangGraph · Workflows using LangGraph · Conditional branches & loops · Build a ReAct Loop using LangGraph

    Output: ReAct Agent Rebuilt in LangGraph


  • Session 8 – Multi Agent Systems

    Introduction to Multiagent Systems · Subagents and hand-offs · Multi-Agent Architectures

    Output: GitHub Agent - Multiagent system for GitHub automation

  • Session 9 – Evals, Guardrails & Observability

    Online vs Offline Evals · Evaluating RAG Pipelines · Evaluating Agents · Guardrails · Interpretation of Evals

    Output: Adding Eval harness to the projects.


  • Session 10 – Multimodal AI

    Architecture of a multimodal AI model · Extract data from PDFs/images · Multimodal RAG System

    Output: Multimodal RAG Extracting Structured Data from Documents

  • Session 11 – Deployment on AWS

    Introduction to AWS's Agent Stack · Deploying LangChain on AgentCore · AgentCore Services

    Output: Your Agent Deployed on AWS AgentCore


  • Session 12 – MCP

    What is Model Context Protocol · MCP Architecture · Building MCP Servers · Building MCP Clients

    Output: Your First MCP Server & Client

  • Session 13 – Context Engineering

    Importance of Context in complex AI Systems · Context Engineering Fundamentals · Improving Context Propagation in your agents · Hands-on with deepagents

    Output: Compound AI system (LangGraph multi-agent + MCP server + RAG) code & LangSmith


  • Session 14 – Fine Tuning & Local AI

    Fine-tune vs RAG: when to opt for what? · LoRA & QLoRA training · Synthetic dataset pipelines · What are SLMs? · Ollama

    Output: Fine-Tuned SLM Running Locally with Ollama

  • Session 15 – Capstone Project Discussion & Assignment Showcase

    Scoping and discussing capstone project ideas · Showcase of assignments/side projects completed so far

    Output: Your Capstone Project Plan


  • Session 16 – AI Product Thinking and Reinforcement Learning

    Turning AI capabilities into usable, valuable products · Thinking like an AI product builder, not just a model user · Core intuition behind reinforcement learning · Reward design for better behaviour

    Output: Product Thinking & Reinforcement Learning Notes

  • Session 17 – Advanced AI Engineering & Security

    Cost optimization at scale · Semantic caching · Smart model routing · OWASP Top 10 for AI · Defending your system from adversarial attacks

    Output: AI Security & Cost Optimization Playbook


  • Session 18 – Stakeholder Management and System Design for AI

    Managing expectations of stakeholders · How an AI System is different · AI System Design Patterns · Production caveats of an AI System

    Output: AI System Design Patterns Reference

  • Session 19 – Voice AI

    Real-time voice stack · Low-latency voice systems · Interruptions & silence handling · Multi-turn context recovery

    Output: Voice agent (<800ms end-to-end, tested on 10 queries)


  • Session 20 – Inference Engineering

    What is Inference Engineering · Runtime Optimizations: batching, caching, quantization, speculation · Infrastructure Optimizations: routing, load balancing, autoscaling · Serving an LLM Endpoint with vLLM

    Output: Local SLM (Qwen 2.5-3B) as a production REST API with vLLM, plus a cost/latency router benchmark

  • Session 21 – Personal Branding & Mock Interview

    LinkedIn & Twitter positioning · GitHub portfolio storytelling · Live Mock Interview with Dhaval Patel & Siddhant Pandey

    Output: Personal Brand & Interview Readiness Checklist

  • Session 22 – Final Project Showcase

    Presenting your capstone project to peers, mentors & industry guests

    Output: Capstone Demo Day

Includes AI Engineering & Data Science Bootcamp 4.0 worth US$345.

The Codebasics Promise

Premium Training, Without The Premium Price.

Other paths can work. Here is exactly what you get from each.

What you get Self-study Other live bootcamps Our live cohort
Live, mentor-led sessions
Real projects shipped to GitHub Rarely Sometimes 6+1 projects
The current 2026 agent stack On your own Often dated
Job assistance
Investment Your time ₹2,00,000+ US$660

May we help you?

Frequently Asked
Questions

Q.1 Do I also get the AI Engineering & Data Science Bootcamp 4.0?

Yes. Every enrollment includes full access to the AI Engineering and Data Science Bootcamp 4.0, worth ₹18,000, at no extra cost.

Saturdays and Sundays, 4–7 PM IST. Sessions are fully live and interactive, with a strong focus on hands-on practice, real-time problem solving, and Q&A. Recordings are available for revision.

All live sessions are recorded and uploaded within 24–48 hours. You can watch them at your own pace.

No. You keep access to all recordings for 1 year from your enrollment date.

The Inner Circle is early enrolment for Cohort 3, open until August 12th, 2026.

You're securing your seat now. Full bootcamp access opens when Cohort 3 officially launches around August 15th, 2026.

AI Engineering & DS Bootcamp 4.0 is self-paced and beginner-friendly, covering AI and Data Science fundamentals from scratch.

AI Engineering Bootcamp is a fast-paced, live cohort for experienced software engineers with 2+ year of experience, that assumes strong programming fundamentals and focuses on AI architecture, system thinking, production engineering & shipping real-world AI systems.

You only pay the difference to upgrade to the AI Engineering Bootcamp Cohort 3. Your existing investment carries forward.

Q.1 Do I need ML experience?

No. If you have at least 2 years of software engineering or coding experience, you're ready. We cover AI from an engineering lens.

We strongly advise against it. This bootcamp moves fast and assumes you can already write code confidently. If you're early in your career, start with the AI Engineering & Data Science Bootcamp first. Build the foundation, then come back.

Software engineers moving into AI roles, developers adding AI to existing products, and tech leads or architects designing AI systems. If you write code for a living and want to build real AI systems, this is for you.

Q.1 Is there job assistance?

The AI Engineering Bootcamp focuses on building your skills, portfolio, and online presence. The AI Engineering & DS Bootcamp (included with your enrollment) has dedicated job assistance: resume builder, LinkedIn optimization, portfolio website, and mock interviews.

Q.1 I already own the AI Engineering & DS Bootcamp 4.0. What do I pay?

The amount you paid for the AI Engineering & DS Bootcamp 4.0 is fully adjusted and deducted from your AI Engineering Bootcamp price.

We don't offer a standalone version. The AI Engienering & DS Bootcamp 4.0 is intentionally bundled as a foundational reference throughout the program. If you already own it, you're eligible for a reduced price and your earlier purchase is not wasted.

Q.1 I used a subsidy (my existing AI Engineering & DS Bootcamp 4.0 or individual course purchase). Can I refund my original purchase after enrolling?

No. Once your existing purchase is applied as a subsidy to reduce your price, that original purchase becomes non-refundable.

You get back the amount you actually paid for the AI Engineering Bootcamp. Your original purchase stays intact and you keep access to it.

Full refund if requested by 17th August 2026. After that date, no refunds are available. Check the complete policy: https://codebasics.io/refund-policy

Full refund, no questions asked, if you request by 17th August,2026. After that, no refunds are available.

Q.1 What do I do on weekdays, after the weekend live sessions?

These are long, technical sessions - what you learn, you need to revise, apply, and build on your own during the week. That takes time, but you're not doing it alone: the Discord stays active all week for doubt-clearing.

You can ask questions anytime on Discord. During live sessions, instructors solve problems in real time. You're never stuck alone.

Q.1 What system configuration do I need?

Recommended:
• OS: Windows 11
• Processor: Intel Core i7 (10th Gen+) or AMD Ryzen 7 (4th Gen+). An i5 works if you're not focused on local model training.
• RAM: 8GB minimum, 16GB recommended
• Storage: 512GB SSD strongly recommended
• GPU: NVIDIA GTX 1660 or higher for deep learning and GPU-accelerated tasks

This covers all bootcamp work comfortably. You'd only need stronger hardware if you plan to fine-tune small LLMs locally.

Q.1 Do I also get the AI Engineering & Data Science Bootcamp 4.0?

Yes. Every enrollment includes full access to the AI Engineering and Data Science Bootcamp 4.0, worth ₹18,000, at no extra cost.

Saturdays and Sundays, 4–7 PM IST. Sessions are fully live and interactive, with a strong focus on hands-on practice, real-time problem solving, and Q&A. Recordings are available for revision.

All live sessions are recorded and uploaded within 24–48 hours. You can watch them at your own pace.

No. You keep access to all recordings for 1 year from your enrollment date.

The Inner Circle is early enrolment for Cohort 3, open until August 12th, 2026.

You're securing your seat now. Full bootcamp access opens when Cohort 3 officially launches around August 15th, 2026.

AI Engineering & DS Bootcamp 4.0 is self-paced and beginner-friendly, covering AI and Data Science fundamentals from scratch.

AI Engineering Bootcamp is a fast-paced, live cohort for experienced software engineers with 2+ year of experience, that assumes strong programming fundamentals and focuses on AI architecture, system thinking, production engineering & shipping real-world AI systems.

You only pay the difference to upgrade to the AI Engineering Bootcamp Cohort 3. Your existing investment carries forward.

Q.1 Do I need ML experience?

No. If you have at least 2 years of software engineering or coding experience, you're ready. We cover AI from an engineering lens.

We strongly advise against it. This bootcamp moves fast and assumes you can already write code confidently. If you're early in your career, start with the AI Engineering & Data Science Bootcamp first. Build the foundation, then come back.

Software engineers moving into AI roles, developers adding AI to existing products, and tech leads or architects designing AI systems. If you write code for a living and want to build real AI systems, this is for you.

Q.1 Is there job assistance?

The AI Engineering Bootcamp focuses on building your skills, portfolio, and online presence. The AI Engineering & DS Bootcamp (included with your enrollment) has dedicated job assistance: resume builder, LinkedIn optimization, portfolio website, and mock interviews.

Q.1 I already own the AI Engineering & DS Bootcamp 4.0. What do I pay?

The amount you paid for the AI Engineering & DS Bootcamp 4.0 is fully adjusted and deducted from your AI Engineering Bootcamp price.

We don't offer a standalone version. The AI Engienering & DS Bootcamp 4.0 is intentionally bundled as a foundational reference throughout the program. If you already own it, you're eligible for a reduced price and your earlier purchase is not wasted.

Q.1 I used a subsidy (my existing AI Engineering & DS Bootcamp 4.0 or individual course purchase). Can I refund my original purchase after enrolling?

No. Once your existing purchase is applied as a subsidy to reduce your price, that original purchase becomes non-refundable.

You get back the amount you actually paid for the AI Engineering Bootcamp. Your original purchase stays intact and you keep access to it.

Full refund if requested by 17th August 2026. After that date, no refunds are available. Check the complete policy: https://codebasics.io/refund-policy

Full refund, no questions asked, if you request by 17th August,2026. After that, no refunds are available.

Q.1 What do I do on weekdays, after the weekend live sessions?

These are long, technical sessions - what you learn, you need to revise, apply, and build on your own during the week. That takes time, but you're not doing it alone: the Discord stays active all week for doubt-clearing.

You can ask questions anytime on Discord. During live sessions, instructors solve problems in real time. You're never stuck alone.

Q.1 What system configuration do I need?

Recommended:
• OS: Windows 11
• Processor: Intel Core i7 (10th Gen+) or AMD Ryzen 7 (4th Gen+). An i5 works if you're not focused on local model training.
• RAM: 8GB minimum, 16GB recommended
• Storage: 512GB SSD strongly recommended
• GPU: NVIDIA GTX 1660 or higher for deep learning and GPU-accelerated tasks

This covers all bootcamp work comfortably. You'd only need stronger hardware if you plan to fine-tune small LLMs locally.

Inner circle price benefit extended until 12th Aug. Save US$180

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