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.

Do I also get the Gen AI & DS Bootcamp?

Yes. Every enrollment includes full access to the Gen AI & Data Science Bootcamp at no extra cost.

When are the live sessions?

Saturdays and Sundays 7–10:30 PM IST. These are the most likely timings. Most of the learning is self-paced - live sessions are for hands-on practice and problem solving.

What if I miss a live session?

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

What happens after the 75 days? Do I lose access?

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

When do I get access?

You're securing your seat. Access unlocks on the 7th March (launch date).

I'm a fresher or have less than 2 years of experience. Can I join?

We strongly advise against it. The bootcamp moves fast and assumes you can already write code confidently. If you're early in your career, consider starting with the Gen AI & Data Science Bootcamp first.

Who is this bootcamp for?

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

How do I get help if I'm stuck?

You can ask questions anytime on Discord. You can also get help during the live sessions where instructors solve problems in real time.

Is there job assistance?

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

I already own the Gen AI & DS Bootcamp. What do I pay?

The amount you paid for the Gen AI & DS Bootcamp is fully adjusted. Your Gen AI Bootcamp purchase amount is deducted from the AI Engineering Bootcamp price.

What's the refund policy?

Full refund, no questions asked, if you request before March 14, 2026 (7 days from the March 7 launch). After March 14, no refunds are available. Read the full refund policy here: https://codebasics.io/refund-policy

I used a subsidy (my existing Gen AI Bootcamp or individual course purchase). Can I refund my original purchase after enrolling in the AI Engineering Bootcamp?

No. Once your existing purchase is used as a subsidy to reduce your AI Engineering Bootcamp price, that original purchase becomes non-refundable. Example: You own the Gen AI Bootcamp and enroll in the AI Engineering Bootcamp at a reduced price. You cannot later refund the Gen AI Bootcamp because it was used to calculate your reduced price.

I used a subsidy and now want to refund the AI Engineering Bootcamp itself. What happens?

You get back the amount you actually paid for the AI Engineering Bootcamp. Your original purchase (e.g., Gen AI Bootcamp) stays intact and you keep access to it.

Can I purchase only the AI Engineering Bootcamp without the GenAI & Data Science Bootcamp?

We completely understand where you're coming from, why pay for something you feel you may not need? Here's the thing: The AI Engineering Bootcamp is an advanced, fast-paced and highly practical program. The GenAI & Data Science Bootcamp is included so you always have a solid reference point for foundational concepts during the live sessions, think of it as your reference library throughout the journey. We don't offer a standalone version at a reduced price as the program is intentionally designed as an integrated experience. That said, if you are already an existing Gen AI & Data Science learner, you are eligible for a reduced price.

What system configuration do I need for the AI Engineer Bootcamp?

✅ Recommended Configuration (for optimal experience) Operating System: Windows 11 Processor: Intel Core i7 (10th Gen or higher) or AMD Ryzen 7 (4th Gen or higher) (If you’re not focusing heavily on Deep Learning & GenAI, an i5 is also sufficient.) Memory (RAM): 8GB (Minimum) / 16GB (Recommended) Storage: 512GB SSD or HDD (SSD is strongly recommended for better speed) GPU: NVIDIA GTX 1660 or higher (e.g., GTX 2060, 3060, or above) for Deep Learning and GPU-accelerated tasks Note: The above configuration is more than enough for all learning and bootcamp work. You would only need stronger hardware if you plan to fine-tune small LLMs locally.

AI Engineering Bootcamp: Become an AI-Enabled Software Engineer who Builds, Orchestrates and Distributes

LIVE Bootcamp Designed & Taught by AI Industry Experts & Engineering Leaders

The AI revolution is here. Engineers who can build with LLMs, design agents, and deploy AI at scale are in the highest demand.

AI Engineering Bootcamp is a LIVE, weekend program transforming experienced developers into AI Engineers. Over 9 weekends, master the full AI stack: RAG, agents, multi-agent systems, MCP, fine-tuning, cost optimisation, observability, and cloud deployment, taught by industry experts trusted by 1M+ learners.

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Weekends

Live Sessions

Real Projects

Capstone Project

1 Year

Access to LIVE Class Recording

130+

Enrolled Learners

AI Engineering Bootcamp: Become an AI-Enabled Software Engineer who Builds, Orchestrates and Distributes

US$630

Created by :

Dhaval Patel & Hemanand Vadivel

Join our Bootcamp

Learn In-demand Skills

Get Hired by Top Companies

Enroll Now

Codebasics Promise

We stand by the quality of our content. Not satisfied? No questions asked refund until 14th March 2026

Added Benefit

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

Download Brochure

Weekends

Live Sessions

Real Projects

Capstone Project

1 Year

Access to LIVE Class Recording

130+

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, Azure AI, 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 optimisation, interview preparation, everything you need to land the AI engineer role

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Bootcamp Journey

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Our Happy Learners

Our content is rated 4.9/5 from 23591+ Learners

Jorge Daniel Carreon Guzman

Data scientist

SQL

Benedict Coltman

Senior Data Scientist

Machine Learning

Abhishek Rajeev

Python

Mansi Agrahari

Data Analyst, Freelancer, Varanasi

SQL

Faizal Ahmed

Sr Manager, Business Analytics

Python

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Completing this course has been an incredibly rewarding experience. Taught by Dhaval Patel, the Deep Learning: Beginner to Advanced course stands out for its clarity, structure, and practical depth.

From the fundamentals of neural networks to the intricacies of CNNs, RNNs, and Transformers, every concept is explained in a way that is accessible yet technically solid. What sets this course apart is the strong focus on hands-on learning — using PyTorch to build real-world projects that reinforce the theory.

Key strengths of the course:
✅ Clear and intuitive explanations
✅ Strong emphasis on real-world applications
✅ Step-by-step PyTorch implementation
✅ Coverage of cutting-edge topics like Transformers
✅ Practical tips and insights drawn from industry experience

Whether you're new to deep learning or looking to strengthen your foundation, this course is an excellent investment of time and effort. I walked away not just with knowledge, but with confidence to apply deep learning in real projects.

A big thank you to Dhaval Patel and the Codebasics team for making deep learning approachable and applicable.

Om Thaware

Deep Learning

Codebasics’ machine learning course is excellent—better than 90% of industry courses. It’s easy to follow, well-structured, and simple to understand. I highly recommend it to anyone interested in learning machine learning and considering building their skills with this course.

Deepak Yadav

Data Analyst

Machine Learning

Landed a Job

Thank you Dhaval Sir and the entire Codebasics team for coming up with such courses which are super rare to find. Totally worth taking it. All the concepts were taught very easily and very intuitively so that we can grasp and digest the fundamentals within no time. The best part I like about the courses on codebasics.io is that they try to replicate real industry experiences in the form of Peter Panday and Tony Sharma. Well done. Keep up the good work. Will take every course from codebasics.io which is relevant for me. Cheers !!

Prateek Pritam

Math & Stats

Landed a Job

This is the best AI course that I have gone through. Thank you Dhaval.
It would be great if you can create advanced courses with hands on real world complex problems to equip certain roles like AI Technical leads, Architects, Technical Managers

Kishor Subbaraman

Hello CodeBasics team and fellow students!

I’ve just completed the Python course from the GEN-AI bootcamp, and I really want to thank Mr. Patel for conducting such engaging lectures and practical sessions. I had the chance to apply what I learned on two real-life projects (I’m saying two because some projects were excluded in GEN-AI, but these two were highly relevant).

The exercises after each unit were a great way to reinforce learning. My advice: take this course and practice consistently. Once you finish the course, keep practicing to truly master the concepts.

Thank you, CodeBasics! I’m proud to be part of this family and to have completed the first step in my GEN-AI/Data Science journey.