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Intermediate 8 weeks 💰 Fee · PKR 30,000

Generative AI & LLM Engineering

Build with the latest LLMs — RAG, fine-tuning, vector DBs, and AI agents.

Program fee

PKR 30,000

or up to 2 installments

Stack: LLM RAG LangChain OpenAI Vector DB Prompt Engineering Embeddings Agents Eval

Live virtual classes

Every evening at 9–11 PM (PKT), plus weekend deep-dives

No prerecorded lectures. Every session is live with a mentor — you ask questions, write code on the call, and get feedback in real time. Weekend sessions are extended deep-dives where you build the week's project end-to-end with the cohort.

Weeknight classes

Monday to Friday · 9–11 PM PKT. Concepts, walkthroughs, mentor Q&A. After your day job or classes.

Weekend deep-dives

Saturday & Sunday · extended hands-on sessions. Ship a working project every weekend with the cohort.

🎥 100% live · Zoom & Google Meet 📼 Recordings if you miss 💬 24h mentor reply on chat

About this program

Every product team needs someone who can ship AI features that actually work — not just chat demos. In 8 weeks you become the person on the team who knows how RAG, agents, fine-tuning, and evaluation actually fit together. Live sessions weeknights 9–11 PM PKT. Weekend builds are where you ship the week's AI feature end-to-end with the cohort — a chat-with-your-docs app, an agent that books meetings, a fine-tune you actually evaluate. We stay rigorous on cost, latency, and evaluation. The world has too many AI demos. We're producing engineers who ship.

What you'll build

Real projects · not toy exercises

⚖️

Model Evaluation Report

Honest side-by-side eval of 3 models on a real task.

🔎

Chat-with-your-docs App

A RAG pipeline with proper chunking, citations, and quality metrics.

🤖

Real Agent

A multi-step agent that books meetings end-to-end (no demo magic).

🛡

Eval Harness

A reusable eval suite to prove an LLM change is actually better.

🚀

Live AI Feature

A deployed, monitored AI feature with feedback collection.

Who this program is for

If any of these sound like you, you're in the right place 👋

✓ You're a software engineer wanting to be the AI specialist at your company.

✓ You're a founder building an AI-first product and need real engineering depth.

✓ You've hit the limits of "prompt engineering" and want to ship real systems.

Course outline

What you'll learn

5 modules · 25 topics · hands-on the whole way.

LLM Foundations

How transformers work
Tokenization & embeddings
Comparing models
Cost & latency tradeoffs
OSS vs hosted models

Prompt Engineering

Prompt patterns
Few-shot examples
Output formatting
Evaluating prompts
Prompt versioning

Retrieval-Augmented Generation

Vector databases
Chunking strategies
Hybrid search
Citation handling
RAG eval

Agents & Tools

Tool use & function calling
Multi-step agents
Memory & context
Guardrails
Failure modes

Productionising AI

Streaming responses
Caching & cost control
Evaluation harnesses
Monitoring & feedback loops
PII & safety

Your roadmap

Week by week, step by step

A clear path — not vibes. You'll know exactly what to ship at every checkpoint.

LLM fluency

Weeks 1-2

Deliverable: Side-by-side eval of 3 models

RAG pipeline

Weeks 3-4

Deliverable: Chat-with-your-docs app

Agents

Weeks 5-6

Deliverable: Agent that books meetings end-to-end

Ship to prod

Weeks 7-8

Deliverable: Public AI feature with monitoring

What changes after

By the last week, you can…

🎯

Build production-grade RAG pipelines with proper chunking, retrieval, and citations.

🎯

Design agents that complete real multi-step tasks reliably.

🎯

Run rigorous LLM evaluations — no "looks good to me" benchmarking.

🎯

Control cost, latency, and quality in production AI systems.

Ready to start Generative AI & LLM Engineering?

Free forever. Mentor-led. Real projects. The kind of program you'd pay for — except you don't have to.

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