Live Cohort
Flagship
Internship Access

2-Month AI Training
+ Internship

Practical, live AI engineering built around daily projects and real deployment — not pre-recorded theory. You finish with shipped work and the interview prep to back it up.

📅 60 days 💻 100% live online 🌐 Worldwide 🔨 Weekly builds
Enquire for Pricing
Talk to an advisor for cohort dates & fees
60 days of live daily training
Weekly project builds + code review
Interview prep & mock sessions
Internship & job access
Freelancing blueprint module
Portfolio & GitHub review

We reply within 2 hours on WhatsApp.

60-Day Breakdown

Full Curriculum

Two distinct months — the first builds your technical foundation, the second launches your career.

M1
Month 1 — Practical AI (Days 1–30)
Daily sessions · AI tools · Intensive project-based learning
📖
Transformer architecture — intuitive deep-dive without heavy math
Lab: First API calls — OpenAI, Anthropic Claude, Google Gemini side by side
📖
Prompt anatomy: system prompts, temperature, token budgets, context windows
Lab: Chain-of-thought, few-shot, structured JSON output patterns
🛠️
Weekly Build: AI-powered Q&A CLI with multi-model switching
📖
Embeddings — what they are, why they work, which model to choose
Lab: Pinecone vector DB setup — embed, upsert, and query real documents
📖
Semantic vs keyword search — hybrid retrieval and re-ranking
Lab: Full chunking → embedding → retrieval pipeline
🛠️
Weekly Build: Private document Q&A chatbot (RAG over your own files)
📖
Agent architecture — ReAct loop, planning, memory, function calling
Lab: Single agent with web search + code execution tools
📖
Multi-agent coordination — supervisors, handoffs, guardrails
Lab: Research agent that autonomously produces a structured report
🛠️
Weekly Build: Autonomous task agent with persistent memory and delegation
📖
FastAPI fundamentals — building LLM-powered REST APIs
Lab: Deploy RAG API with streaming responses to a live URL
📖
Evaluation & observability — hallucination detection, latency, cost
Lab: Logging, error handling, rate limiting on production endpoints
🛠️
Month 1 Capstone: Full-stack AI app — live URL, documented API, public repo
M2
Month 2 — Career Focus (Days 31–60)
Interview prep · Internship access · Placement & freelancing
Live mock technical interviews with instructor feedback
📖
Common AI/ML interview patterns — architectures, tradeoffs, system design
Code-along drills — data structures and algorithms with AI assistance
🛠️
Build: Personal answer framework + question bank from your own projects
GitHub profile teardown — what hiring managers actually look at
📖
Writing READMEs that tell a story and demonstrate depth
Deploy personal portfolio site featuring all program projects
🛠️
Build: Polished portfolio with 3 deployed AI projects + live demos
Introduction to openings in the Ujar ecosystem
📖
Placement drive structure — what to expect, how to prepare
Resume tailoring for AI/ML internship and junior roles
🛠️
Live placement sessions with real employer feedback
📖
Positioning as an AI freelancer — what clients pay for
Platform strategy: Upwork, Toptal, direct outreach — picking your path
📖
Scoping, pricing, and delivering AI projects for clients
🛠️
Final capstone: Public case study + pitch deck of your best project
Tangible Deliverables

What you build & ship

By the end you have a portfolio of real, deployed work — running code with live URLs, not slide decks.

🤖
Autonomous AI Agent

Multi-step agent with tool use, persistent memory, and delegation — deployed via API with documentation.

🔍
RAG Knowledge System

Private document Q&A — vector embeddings, semantic chunking, hybrid retrieval, live chatbot interface.

🌐
Full-Stack AI Web App

LLM-powered web application with streaming responses, deployed with a real URL you can share.

📁
Public GitHub Portfolio

Clean, well-documented GitHub profile with commit history and live demo links employers can inspect.

📄
Case Study + Pitch Deck

Written technical writeup of your best project — ready to share with any employer or prospective client.

🎯
Interview Framework

Tested answers to 30 common AI/ML interview questions, personalised around your actual projects.

Technical & Career Skills

Skills you walk away with

LLM APIs (OpenAI · Claude · Gemini)Prompt EngineeringVector DatabasesRAG SystemsLangChainAutonomous AgentsTool CallingFastAPIPython (intermediate)Docker basicsGit & GitHubTechnical WritingInterview PreparationPortfolio BuildingFreelancing Strategy

LLM Engineering

Calling, prompting, evaluation, and production monitoring of large language models across multiple providers.

🔍

Retrieval Systems

Vector search, embedding models, chunking strategies, hybrid retrieval, and re-ranking pipelines.

🤖

Agent Development

Agentic loops, multi-step planning, tool use, memory management, and multi-agent coordination.

Ideal Learner

Who this program is for

🎓

Students

Build a portfolio that stands out before you graduate. No prior AI experience needed — we start from fundamentals and move fast.

💼

Early-Career Professionals

Add AI skills to your existing experience. Learn to apply AI to real problems, not just understand it theoretically.

🔄

Career Switchers

Pivot into AI engineering. Designed to give enough depth in 60 days to compete for entry-level AI roles.

🌐

Freelancers

Add AI capabilities to your services. Month 2 includes a full freelancing blueprint for acquiring and delivering AI client work.

Not right for you if…

You want a self-paced course to watch on weekends without daily commitment. This requires 2–4 hours per day. If that's not feasible, start with our weekly workshops instead.

Common Questions

FAQ — AI Program

Basic Python familiarity helps but isn't required. We cover the Python you need in week one. The focus is on using AI APIs and frameworks — not low-level computer science.

Roughly 1.5–2 hours of live instruction per day, plus project time on your own schedule. Most learners spend 3–4 hours per day total including labs and builds.

Yes. Recordings are available to enrolled learners. We strongly encourage attending live for the interactive benefit, but recordings are there if you miss a session.

You retain community access and recordings. Internship and job openings are shared transparently with alumni as they arise. We don't guarantee placements, but we actively share openings and support applications.

Yes. The program is 100% online and open worldwide. Session times are listed in IST — message us on WhatsApp to discuss your timezone before enrolling.

If you can learn from written instructions and commit 2–4 hours per day, you're ready. Message us on WhatsApp — we'll have a quick 10-minute chat to confirm fit before you enroll.

Ready to build with AI?

Send your application — we'll confirm cohort dates and answer questions on WhatsApp within 2 hours.