Sit in on a live demo class with the instructors. If it clicks, join the bootcamp after the demo at the Diwali price of ₹9,999₹14,999. If not, you’ve lost nothing.
Saturday, 14 November · 11:00 AM IST · Live online
A live demo class with the bootcamp’s instructors
See how the 16 weeks are taught, and what you will build
Ask your questions live, before you decide anything
Like it? Join the bootcamp after the demo at the Diwali price of ₹9,999 (instead of ₹14,999). If not, you’ve lost nothing.
Reserve your free seat
Overview
An instructor-led programme for engineers moving into AI. Two hours of live class every weekday, daily assignments, one mini project every week, a doubt session every weekend, and a production-minded capstone you present at the end. Every class is recorded, and you keep the recordings and the community for 12 months.
Monday to Friday · 8:00 to 10:00 PM IST
Live over video, two hours a day · daily assignments · one mini project a week
4 months · 16 weeks · 96 topics
Taught live, with questions answered in class
Preview sessions
1 video · Naresh Edagotti
Watch how a class is taught before you enrol.
Preview 1
Preview session: how the bootcamp runs
Curriculum
4 months · 16 weeks · 96 topics
Four months, one theme a month. Every week is five live classes with a daily assignment, one mini project built from that week’s topics, and a doubt session at the weekend. AI engineering evolves rapidly, with new developments emerging weekly, so the curriculum may be updated to reflect relevant advances and changing industry needs.
The full curriculum, week by weekPDF · 10 pages · every topic and the monthly goalsView PDFDownload
Month 1Programming and AI Foundations4 weeks · 23 topics
Build confidence with Python, developer workflows, APIs and databases; understand LLM fundamentals and create a first AI-powered application.
Week 1Python Programming Basics
Developer environment and terminal
Variables and data types
Conditionals and loops
Collections
Functions, modules and debugging
Mini project of the week
Week 2Practical Python and Developer Tools
File handling and JSON/CSV
Object-oriented programming
Virtual environments and packages
Git and GitHub
Type hints, validation and unit testing
Mini project of the week
Week 3APIs, Backend Development and Data
HTTP and REST concepts
External API integration
Authentication and error handling
FastAPI fundamentals
SQL, SQLite and CRUD operations
API testing
Mini project of the week
Week 4Generative AI and LLM Fundamentals
AI, ML and generative AI overview
Transformers and tokens
Model capabilities and limitations
LLM APIs
Prompt and context basics
Structured outputs
Simple AI interfaces
Mini project of the week
Month 2LLM Applications and AI Agents4 weeks · 24 topics
Engineer reliable LLM applications, retrieval systems and agents capable of using tools and interacting with external systems.
Week 5LLM Application Engineering
Context engineering and prompt design
Conversation history
Structured data extraction
Streaming and caching
Model selection, cost and latency
Tool and function calling
Mini project of the week
Week 6Retrieval-Augmented Generation
Embeddings and semantic search
Document parsing and chunking
Vector databases
Retrieval pipelines
Hybrid retrieval and reranking
Citations and RAG evaluation
Mini project of the week
Week 7Building AI Agents from Scratch
Workflows versus agents
Agent execution loops
Planning and tool selection
Custom tool definitions
State and termination rules
OpenAI Agents SDK and tracing
Mini project of the week
Week 8MCP and Agent Integrations
Model Context Protocol architecture
MCP clients and servers
Exposing Python tools
Tool discovery and validation
External API integrations
Credentials, approvals and auditability
Mini project of the week
Month 3Advanced Agentic System Engineering4 weeks · 25 topics
Design stateful and multi-agent workflows with persistence, human oversight, evaluation, and robust security practices.
Week 9Stateful Agent Orchestration
LangGraph concepts
Nodes, edges and state
Conditional routing
Checkpointing and durable execution
Human-in-the-loop interrupts
Recovery and workflow testing
Mini project of the week
Week 10Multi-Agent System Design
Single-agent versus multi-agent architectures
Specialist roles and handoffs
Supervisors and delegation
Shared versus isolated context
Parallel tasks
Coordination and cost trade-offs
Mini project of the week
Week 11Memory and Long-Running Agents
Short-term and long-term memory
Persistent memory stores
Summarization and retrieval
Background jobs and queues
Scheduling and webhooks
Sandboxed skills
Resumable execution
Mini project of the week
Week 12Evaluation, Observability and Safety
Evaluation datasets and metrics
Model and tool-use assessments
Tracing and telemetry
Prompt injection and untrusted input
Least-privilege tools
Guardrails, regression tests and incident handling
Mini project of the week
Month 4Production Applications and Capstone4 weeks · 24 topics
Integrate agents into full-stack products, deploy and monitor them, and demonstrate a production-minded end-to-end capstone.
Week 13Production Backend and Deployment
Agent APIs with FastAPI
Asynchronous execution and streaming
Docker and Compose
PostgreSQL migrations
Environment and secret management
Cloud deployment and CI/CD
Mini project of the week
Week 14Full-Stack AI Products and Operations
Agent user experience
Streamlit and frontend integration
File upload and progress tracking
Authentication and authorization
Rate limits
Monitoring, cost controls and end-to-end tests
Mini project of the week
Week 15Capstone Development
Problem definition and requirements
Architecture and data flow design
Agent workflows and integrations
Retrieval and persistence where appropriate
User interface
Iterative code review
Mini project of the week
Week 16Reliability, Final Delivery and Presentation
Security and reliability improvements
Evaluation and performance review
Documentation and architecture diagrams
Final deployment
Product demonstration
Technical presentation and portfolio readiness
Mini project of the week
How a week runs
1Live class, Monday to FridayTwo hours in the evening with the instructor: concepts, a worked build, and your questions answered as they come up.
2Daily assignmentA short assignment after every class, so each topic is practised the day it is taught.
3One mini project every weekYou build one small project from the week's topics, every week of the batch.
4Doubt session at the weekendEvery weekend, a live session to clear the week's doubts before the next week starts.
5Recordings for 12 monthsEvery class is recorded and stays available to you, with the community, for 12 months.
6Capstone in month 4Weeks 15 and 16 are yours: define a problem, build it, deploy it and present it to the batch.
Tools you will use
Python 3
Git and GitHub
FastAPI
SQL, SQLite and PostgreSQL
LLM APIs
OpenAI Agents SDK
Model Context Protocol
LangGraph
Vector databases
Docker and Compose
Streamlit
CI/CD and cloud deployment
What you will be able to do
Write and test Python the way a working engineer does, with Git, packages and a debugger
Build and ship a backend with FastAPI, SQL and real external APIs
Build retrieval systems with embeddings, vector databases, reranking and evaluation
Build agents from scratch, then with the OpenAI Agents SDK, MCP and LangGraph
Design multi-agent systems with memory, human oversight, guardrails and tracing
Deploy an agentic product with Docker, PostgreSQL, CI/CD and monitoring
Present a production-minded capstone you can put in front of an interviewer
Who it is for
This batch is for
Working engineers moving into AI engineering
Graduates and career switchers who can give two hours every weekday
Developers already calling LLM APIs who want agents, RAG and production depth
Before you join
A laptop you can install software on
Two hours free on weekday evenings, and a few more at the weekend
No programming experience needed: month 1 starts from the terminal
Not for someone who wants to watch at their own pace. The batch moves together; if evenings are not possible, the self-paced courses are the better fit.
Your instructors
3 instructors
Three working AI engineers teach the batch together, each from the systems they build at work.
Came to AI from automotive engineering and full-stack development, where he built and scaled MERN applications. Now designs agentic AI workflows and production LLM applications, and helps companies bring AI automation into real systems.
An AI engineer focused on generative AI, LLMs, RAG and AI agents, and the creator of PracticAI. Shares what he builds and learns every day with a large community of engineers, and has written more than 25 AI courses.
Builds production-grade AI for enterprises: agent orchestration platforms with workflow execution, evaluation and observability. Before that, ML and generative AI work in insurance and IT service management, from predictive models to semantic search.
Multi-agent systems
MLOps and observability
Enterprise RAG
FastAPI and cloud
Enterprise AI platforms
GCP and Azure
Questions people ask
What if I miss a class?
Every class is recorded and you keep access to the recordings and the community for 12 months. Bring anything you are stuck on to the weekend doubt session, so you can catch up before Monday.
Do I need to know programming?
No. Month 1 starts from the terminal and basic Python. If you already code, the first weeks go quickly and the pace picks up from week 3.
How are classes delivered?
Live over video, two hours each weekday evening in India time. The joining link and the class calendar reach your email before the first class.
Is there a certificate?
Yes, a certificate of completion at the end of the batch for everyone who completes the capstone.
Can I get a refund?
Yes, within the refund window from purchase, requested from your account page, the same as every course here. After classes start, write to support and we will look at it case by case.
Is this part of a membership plan?
No. A live course is bought on its own, one payment for the whole batch. Plans cover the self-paced courses, projects and interview kits.
How can I pay?
In one payment through Razorpay, by UPI, card, net banking or any other method Razorpay offers you. The invoice reaches your email as soon as the payment clears.