Python Full Stack + AI 
Developer Program
(Python + Django + ReactJs + REST API + AI + Git)

Introduction to Python and setup

Data types (int, float, str, bool, list, tuple, set, dict)

Variables and basic operations

Conditional statements (if, else, elif)

Loops (for, while)

Functions and scope

Basic input/output

Advanced OOP concepts (inheritance, polymorphism, encapsulation, abstraction)

Decorators and generators

Iterators and comprehensions

Working with *args and **kwargs

Working with dates and times

Lambda functions, map, filter, and reduce

Setting up Django environment

Django project structure

Creating your first Django app

Understanding models, views, and templates (MVT pattern)

Django admin interface

URL routing and request handling

Creating and processing forms

Form validation and custom validations

Django user authentication system

User registration, login, logout

Password management and profile management

Implementing user roles and permissions

Introduction to RESTful principles

Setting up Django Rest Framework

Creating serializers and views

Building simple APIs with DRF

Handling GET, POST, PUT, DELETE requests

Setting up Django to serve ReactJS (or other frontend frameworks)

Building a basic frontend interface

Connecting frontend to Django backend via APIs

Handling CORS issues

Basic frontend-backend authentication integration

Introduction to ReactJS and setup

Understanding JSX

Components, props, and state

Functional vs. class components

Handling events in React

Conditional rendering

Fetching data from Django REST API

Handling API calls with fetch and axios

Managing loading and error states

Displaying data in lists and tables

Form submission to the backend

Authentication in React using JWT (JSON Web Tokens)

Understanding AI, Machine Learning (ML), and Deep Learning

Supervised vs Unsupervised Learning

Setting up AI development environments (Jupyter, Google Colab, TensorFlow, PyTorch)

Python libraries for AI: NumPy, Pandas, Matplotlib, Scikit-Learn

Data preprocessing & feature engineering

Introduction to Artificial Neural Networks (ANN)

Understanding activation functions, forward & backward propagation

Hands-on: Building a simple neural network using TensorFlow/Keras

Introduction to Convolutional Neural Networks (CNN) for image recognition

Hands-on: Implementing an image classifier

Lists, tuples, and dictionaries in depth

List comprehensions

String manipulation

Exception handling

Modules and packages

File handling (reading/writing files)

Introduction to object-oriented programming (OOP)

Introduction to libraries: NumPy, Pandas

Data analysis with Pandas

Working with CSV, JSON, and Excel files

Basic data visualization with Matplotlib and Seaborn

Introduction to databases and MySQL in Python

Defining models and fields

Working with the Django ORM (Object-Relational Mapping)

CRUD operations with Django models

Migrations and database schema management

Using MySQL and connecting to MySQL

Querying the database

Django signals and middleware

Static files and media files handling

Customizing Django admin interface

Pagination in Django

Sending emails with Django

Deploying Django applications (introduction)

Authentication and permissions in DRF

Token-based authentication

ViewSets and routers

Pagination, filtering, and ordering in DRF

Testing APIs with tools like Postman

Introduction to version control and Git

Installing and configuring Git

Git basic commands: init, clone, add, commit, push, pull

Branching and merging in Git

Working with GitHub: repositories, forking, pull requests

Collaboration workflows with Git (e.g., Gitflow)

React component lifecycle methods (class components)

Using useState and useEffect hooks

Forms in React and handling input

Lifting state up and component communication

React Router for single-page applications (SPA)

State management with Context API and basic Redux

Designing the app structure

Backend: Building the API with Django

Frontend: Creating the UI with React

Integration: Connecting frontend with backend

Version control with Git and GitHub

Deploying the full-stack application (AWS, or other platforms)

Final project presentation and review

Building regression and classification models (Linear Regression, Decision Trees, Random Forest, SVM)

Model evaluation: Accuracy, Precision, Recall, F1-Score

Hyperparameter tuning and cross-validation

Hands-on: Building an ML model for real-world datasets

NLP (Natural Language Processing) basics: Tokenization, Lemmatization, Sentiment Analysis

Hands-on: Building a chatbot using Python & NLP

AI in software testing: Visual testing, anomaly detection, self-healing automation

Final project: Implementing an AI-driven application (e.g., chatbot, recommendation system, or automated testing suite)