Python AI & Deep Learning Roadmap

Python Fundamentals

Syntax, variables, data types, operators, input/output, program structure.

Control Flow & Functions

Conditions, loops, functions, recursion, basic problem solving.

Checkpoint — Python Basics

Data Structures

Lists, tuples, sets, dictionaries, comprehensions.

OOP in Python

Classes, objects, inheritance, encapsulation, polymorphism.

Checkpoint — Programming Foundations

NumPy

Arrays, vectorization, mathematical operations, broadcasting.

Pandas

DataFrames, data cleaning, manipulation, feature engineering.

Checkpoint — Data Handling

Data Visualization

Matplotlib, Seaborn, plots, charts, insights.

Statistics for AI

Probability, distributions, hypothesis testing, correlations.

Checkpoint — Analytical Foundations

Machine Learning

ML Fundamentals

Supervised & unsupervised learning, ML pipeline.

ML Algorithms

Regression, classification, clustering, KNN, SVM, trees.

Checkpoint — Core ML

Deep Learning

Neural Networks

Perceptron, activation functions, backpropagation.

Deep Learning Frameworks

TensorFlow, Keras, PyTorch basics.

Checkpoint — Deep Learning Core

Computer Vision

CNNs, image classification, OpenCV.

Natural Language Processing

Text processing, RNNs, Transformers, embeddings.

Checkpoint — Advanced AI

Model Deployment

Flask/FastAPI, REST APIs, model serving.

AI Capstone Project

End-to-end AI/DL project with real-world use case.

Industry Ready AI & DL Engineer