Python-and machine learning basics

Stage 1: Python Foundations
Total Duration: 4 Weeks Topic 1: Python Fundamentals — 1 Week
Subtopics & Duration:
Installing Python, IDEs (VS Code, Jupyter) – 0.5 days
Data Types, Variables, Operators – 1 day
Input/Output, Type Casting – 0.5 day
Control Flow: if/else, loops, break, continue – 2 days
Practice + Review – 2 days
Mini Project: Password Strength Checker
Topic 2: Data Structures & Functions — 1 Week
Subtopics & Duration:
Lists, Tuples, Sets, Dictionaries – 2 days
Functions: Arguments, Return Values, Scope – 2 days
Modules and Packages – 2 days
Practice – 1 day
Mini Project: Log Cleaner Script
Topic 3: File Handling & OS Automation — 1.5 Weeks
Subtopics & Duration:
Reading/Writing txt, csv, json – 2 days
Exception Handling (try/except, custom exceptions) – 2 days
OS and Time Modules – 2 days
Review and Practice – 1–2 days
Mini Project: Filesystem Integrity Monitor
Expectations for Stage 1
Good Programmer: Can write simple scripts and automate basic tasks
Brilliant Programmer: Modular code, strong error handling, file operations, and CLI design
Extraordinary Programmer: High-quality reusable code with strong input validation and system awareness

Stage 2: Applied Programming
Total Duration: 3 Weeks
Topic 4: Networking and Web Basics — 1 Week
Subtopics & Duration:
IP, Port, HTTP Theory – 1 day
Web Requests with requests – 2 days
Web Scraping – 1 day
Sockets and Client-Server basics – 2 days
Practice – 1 day
Mini Project: Website Status Dashboard
Topic 5: Data Visualization & Pandas — 2 Weeks
Subtopics & Duration:
Pandas: Read, Clean, Transform – 4 days
Matplotlib: Line, Bar, Pie Charts – 3 days
Seaborn: Heatmaps, Pairplots – 3 days
Practice – 3 days
Mini Project: Logins Visual Dashboard
Expectations for Stage 2
Good Programmer: Makes working scripts that fetch and visualize external data
Brilliant Programmer: Can create full dashboards, clean data sources, and write modular automation
Extraordinary Programmer: Can integrate data pipelines with real-time feeds, APIs, and scalable utilities

Stage 3: AI + Cybersecurity
Total Duration: 3–4 Weeks
Topic 6: AI/ML Fundamentals — 2 Weeks
Subtopics & Duration:
ML Concepts: Supervised/Unsupervised – 2 days
Numpy & Scikit-learn Basics – 3 days
Training ML Models (Regression, Tree, SVM) – 5 days
Practice – 3 days
Mini Project: Threat Classification Model from CSV Logs
Topic 7: Cybersecurity Essentials — 1.5 Weeks
Subtopics & Duration:
Regex for Logs & IOCs – 2 days
Hashing & Base64 Encoding – 2 days
Threat Intelligence APIs – 2 days
Automation with Email/Slack Bots – 3 days
Mini Project: IOC Extractor & Auto-Alert Script
Expectations for Stage 3
Good Programmer: Understands basic ML and security automation
Brilliant Programmer: Integrates data + ML into security pipelines
Extraordinary Programmer: Builds intelligent security tools from scratch

Final Capstone Project
Title: Lightweight Threat Detection System
Ingest logs
Extract Indicators of Compromise (IP, URLs, Hashes)
Predict severity using ML model
Alert and generate visual reports