Python for AI & Machine Learning — Complete Guide

What You'll Learn

This course covers the complete AI/ML journey — from Python basics to deploying production ML models.

Module 1: Python Foundations

Python programming essentials

Data structures and algorithms

Object-oriented programming

NumPy and Pandas for data manipulation

Module 2: Mathematics for ML

Linear algebra essentials

Probability and statistics

Calculus fundamentals

Optimization techniques

Module 3: Machine Learning

Supervised learning (regression, classification)

Unsupervised learning (clustering, dimensionality reduction)

Feature engineering and selection

Model evaluation and cross-validation

Scikit-learn practical projects

Module 4: Deep Learning

Neural network fundamentals

CNNs for computer vision

RNNs and LSTMs for sequences

Transfer learning

TensorFlow and PyTorch implementations

Module 5: Generative AI & LLMs

Transformer architecture

Working with OpenAI, Gemini APIs

LangChain for LLM applications

RAG (Retrieval-Augmented Generation)

Fine-tuning pre-trained models

Module 6: MLOps & Deployment

Model serving with FastAPI

Docker containers for ML

Cloud deployment (AWS SageMaker, GCP)

Model monitoring and retraining

Career Outcomes

Build and deploy production ML models

Work as an AI/ML engineer or data scientist

Expected salary: PKR 80,000–500,000+/month depending on experience

Python for AI & Machine Learning — Complete Guide

Skills You'll Learn

💡 Why Learn This?

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