All programs

Intermediate 12 weeks 💰 Fee · PKR 20,000

AI & Machine Learning

Master AI fundamentals, deep learning, neural networks, and ship real intelligent systems.

Program fee

PKR 20,000

or up to 2 installments

Stack: Python TensorFlow PyTorch scikit-learn Deep Learning NLP Computer Vision MLOps FastAPI

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

Most people studying "AI" never train a real model. By week 12 you will have shipped three — a classifier behind a public REST API, a deep-learning vision model with > 90% test accuracy, and a fine-tuned transformer your friends can actually use. Every weeknight you join a live 9–11 PM PKT session: 30 minutes of concepts, 90 minutes of code on the call, mentor feedback in real time. On weekends you build the project end-to-end with the cohort. No prerecorded courses, no copy-paste notebooks. You bring solid Python and the willingness to break things. We bring the structure, the projects, and a senior ML engineer who actually reviews your code.

What you'll build

Real projects · not toy exercises

📊

EDA & Insights Notebook

Full exploratory analysis on a real dataset — published as a public Kaggle/Colab link.

🧠

Classifier behind a REST API

Train, evaluate, package, and serve a sklearn model with FastAPI + Docker.

👁

CNN Vision Model

Image classifier with > 90% test accuracy, deployed to a HuggingFace Space.

🗣

Fine-tuned LLM

Fine-tune a transformer on your own domain corpus — proper eval, no demoware.

📈

MLOps Monitoring Dashboard

Track drift, latency, and accuracy of your live model. Looks like real production.

🎓

Public Portfolio

3 deployed demos with public URLs to put on your CV and LinkedIn.

Who this program is for

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

✓ You can write Python loops, functions, and classes — but you have never trained a model end-to-end.

✓ You finished a Coursera ML course and still feel "I don't actually know how to ship this".

✓ You're a software engineer trying to break into ML/AI roles.

✓ You want to apply for AI engineer / ML engineer jobs and need a portfolio that proves you can ship.

Course outline

What you'll learn

6 modules · 30 topics · hands-on the whole way.

Foundations of ML

Python for ML
NumPy & Pandas
Linear algebra refresher
Probability & statistics
Reproducibility & seeding

Data & Feature Engineering

Cleaning real-world data
Categorical encoding
Imbalanced datasets
Feature stores 101
Data leakage traps

Classical Machine Learning

Regression & classification
Decision trees & random forests
Gradient boosting (XGBoost)
Cross-validation done right
Model interpretability with SHAP

Deep Learning

Neural networks from scratch
TensorFlow / PyTorch
CNNs for vision
RNNs & transformers
Training stability & schedulers

Applied AI & LLMs

NLP with transformers
Fine-tuning & LoRA
Computer vision projects
Bias, ethics & evaluation
When NOT to use AI

Production & MLOps

Model serving (FastAPI)
MLOps basics
Docker for ML
Monitoring deployed models
A/B testing model versions

Your roadmap

Week by week, step by step

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

Cohort kickoff & setup

Week 0

Deliverable: Working Python/CUDA/notebook environment, GitHub repo set up

Math + Python under your fingers

Weeks 1-2

Deliverable: Notebook with end-to-end EDA on a real dataset

Build classical ML models

Weeks 3-5

Deliverable: Trained classifier shipped behind a REST API

Move to deep learning

Weeks 6-8

Deliverable: CNN image classifier with > 90% test accuracy

Specialise — NLP or CV

Weeks 9-10

Deliverable: Transformer fine-tuned for a domain task

Ship to production

Weeks 11-12

Deliverable: Live demo with public URL + GitHub repo

Cohort demo day + interviews

Demo week

Deliverable: Recorded 5-min product demo + mock interview pass

What changes after

By the last week, you can…

🎯

Train, evaluate, and deploy ML models end-to-end without holding your hand.

🎯

Read and reproduce a recent ML paper — not just import a library.

🎯

Argue tradeoffs between classical ML, deep learning, and LLMs for any business problem.

🎯

Pass a senior ML interview: theory, coding, and case-study system design.

🎯

Walk into a hiring panel with three deployed demos and an honest evaluation story.

Ready to start AI & Machine Learning?

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

Explore more

Other tracks

View all programs →

Intermediate PKR 40,000

DSA & Interview Prep

Crack technical interviews — DSA patterns, mock interviews, and behavioral prep.

⏱ 10 weeks

Advanced PKR 40,000

Microservices & System Design

Design and ship distributed systems — and ace senior backend interviews.

⏱ 10 weeks

Beginner PKR 30,000

Digital Marketing

SEO, social media, content strategy, Google Ads, and analytics that drive results.

⏱ 8 weeks