Cohort 2 is now Live
Limited seats left, you can still enroll
03
Days
07
Hours
47
Minutes
07
Second
Companies Hiring AI Engineers
What you will build inside Cohort 2?
AI Agent
Memory & Tool Powered Chatbot
Create chatbots that retain conversation history and respond contextually.
MCP & Multi-Agents
Integrate external APIs like weather or search to make AI truly interactive.
RAG & Fine Tuning
Build and deploy hands-on AI applications to strengthen your portfolio.
Your Role is Evolving!
AI Engineer embodies and integrates all the skills—sitting at the intersection of Engineering, AI, and Product.
The Modern AI Engineer's Tech Stack
Traditional Tech Stack
REST APIs
MongoDB
PostgresSQL
Axios
React
Docker
Next Gen AI Tech Stack
ChatGPT
Langchain
VAPI
Weaviate
Fast API
Whisper AI
Orientation:
AI Engineering
Watch Video
Who is this course for?
Working professionals in techFinal-year engineering or CS gradsAnyone who knows basic programmingSuccess Stories from Cohort 1
Tashvik Shrivastava
My intention behind joining the program to strengthen my AI foundations and learn structured ways to build real-world systems. Clear sessions with Vivek Sir and hands-on projects made theory practical. The focus on engineering principles and best practices gave me clarity, skills, and confidence.
Gagan Agrawal
I joined the program for a roadmap on learning the fundamentals, as keeping up with new AI tools becomes impossible. I loved the concept of breakout rooms, hands-on opportunities while sticking to fundamentals. I now feel more confident in experimenting and creating something using AI, while I still keep learning new things.
Krishan Kumar Pareek
MCP was my favorite, it showed how simple yet powerful automation can be. It boosted my confidence that complex systems are achievable with the right setup. Prompt engineering was eye-opening; I learned strategies like examples, step-by-step, and “think” prompts. Practical tips, like splitting chats to manage context and cost, changed my AI habits. Breakout rooms and live interactive sessions enriched the learning experience.
Tushar Mahajan
I enrolled in this program to learn how to apply AI models in real projects. While I had theory, I lacked confidence in execution. The blend of AI and software engineering made it practical and doable. Thanks to this, I built an OnCall Agent at production scale—something I never imagined before!
Paramita Paul
The hands on part and the homeworks given that makes us try a bit on our own even if we don't get it right always is the best thing about this cohort. Also the way Vivek explains everything is awesome. I feel I myself need to give more time on this but I'm finding these classes super interesting
Course Curriculum
1. LLMs Made Simple
Understand how GPT predicts words, learns from text, and improves via human feedback.
2. Inside GPT Models
Learn transformers, tokens, embeddings, attention, and what makes GPT "think"
3. OpenAI API Mastery
Make API calls, use system/user prompts, and build context-aware chat agents.
4. Prompt Engineering
Craft effective prompts using proven techniques for better outputs
5. Tool Calling in Action
Connect GPT to real tools like calculators, search, PDFs, and build functional agents.
6. Agent Workflows
Use prompts + routing to build smart, modular AI agents that perform tasks.
7. RAG & Vector Search
Add memory using vector DBs and Retrieval-Augmented Generation with HyDE and re-ranking
8. Multi agent systems and MCP
Build advanced agents LangChain, CrewAI, LangGraph, Model Context Protocol and browser automation.
1. What is AI Engineering?
AI Engineering is the discipline focused on designing, building, and integrating AI solutions—combining software engineering, AI technologies, and an understanding of user and business needs.
