90-Day Python Learning Plan Recommended pace: 1.5–2.5 hours/day (10–15 hours/week) Goal: Build a strong Python foundation, create real-world projects, and prepare for advanced fields like web development, data science, AI, or automation. 1. Overview What is Python? Python is a high-level, easy-to-read programming language used for: Web development Automation Artificial Intelligence Machine Learning Data Science Cybersecurity Desktop applications Game development APIs Cloud computing Why Learn Python? Python is one of the world's most popular programming languages because it is: Beginner-friendly Powerful Extremely versatile Used by startups and Fortune 500 companies Highly demanded in the job market Supported by an enormous community Expected Learning Outcomes By the end of this roadmap, you'll be able to: Write clean Python programs Build command-line applications Work with files and APIs Understand Object-Oriented Programming Debug code efficiently Use Git for version control Build portfolio-worthy projects Continue into AI, Web Development, or Data Science 2. Prerequisites Knowledge Required Basic computer skills Comfortable using folders and files Basic internet browsing No programming experience required. Tools Needed Python 3.x Visual Studio Code Git GitHub account Terminal or Command Prompt Web browser Recommended Setup Install: Python VS Code Python Extension Git GitHub Desktop (optional) Create folders: Python-Learning/ Week1/ Week2/ Projects/ 3. Weekly Learning Roadmap Week 1 — Python Fundamentals Objective Understand Python basics. Topics Installing Python Variables Data types Printing User input Operators Concepts Integers Floats Strings Booleans Comments Exercises Temperature converter BMI calculator Simple calculator Mini Project Student Grade Calculator Study Time 10–12 hours Week 2 — Control Flow Topics if elif else Loops range() break continue Exercises Guess the number Password checker Multiplication table Mini Project Number Guessing Game Study Time: 12 hours Week 3 — Functions & Collections Topics Functions Lists Tuples Dictionaries Sets Exercises Shopping list Student database Calculator with functions Mini Project Contact Book Study Time 12–15 hours Week 4 — Strings & File Handling Topics String methods File reading Writing files Exception handling Exercises Word counter Log analyzer File organizer Mini Project Personal Diary App Study Time 12 hours Week 5 — Modules & Packages Topics Import Standard library pip Virtual environments Learn random math datetime os pathlib Mini Project Password Generator Week 6 — Object-Oriented Programming Topics Classes Objects Inheritance Encapsulation Polymorphism Mini Project Library Management System Week 7 — APIs & JSON Topics JSON REST APIs requests Exercises Weather API Currency API Mini Project Weather Dashboard Week 8 — Automation Topics Automating files Email automation Excel basics Mini Project Bulk File Renamer Week 9 — Testing & Debugging Topics unittest Debugging Logging Mini Project Expense Tracker Week 10 — Databases Topics SQLite CRUD Mini Project Inventory Manager Week 11 — Git & GitHub Topics Git basics Branches Commits Pull Requests Mini Project Publish all previous projects Week 12 — Capstone Project Choose one: Personal Finance Tracker Task Manager Chat Application Weather Dashboard Quiz System Library System Week 13 — Portfolio & Career Topics Resume GitHub portfolio Documentation Deployment 4. Daily Study Schedule Day Structure (Repeat Daily) 1. Learn (30–45 min) Read documentation or watch tutorials. 2. Practice (45–60 min) Write code without copying. 3. Build (30–45 min) Create a small feature or mini-project. 4. Review (15 min) Fix bugs Take notes Refactor code 5. Challenge (15–30 min) Solve one coding problem. Example Week 1 Schedule Day 1 Install Python Install VS Code Hello World Variables Practice: Print personal information. Day 2 Numbers Strings Input Practice: Age calculator Day 3 Operators Practice: Calculator Day 4 Booleans Practice: Eligibility checker Day 5 Review Practice: Five beginner exercises Day 6 Mini Project Student Grade Calculator Day 7 Revision Complete coding challenges. 5. Best Resources Books Python Crash Course — Eric Matthes Automate the Boring Stuff with Python — Al Sweigart Fluent Python — Luciano Ramalho Think Python — Allen Downey Free Courses Harvard CS50P freeCodeCamp Python Course Python for Everybody Kaggle Python Course Paid Courses Complete Python Bootcamp (Udemy) 100 Days of Code: Python (Udemy) Python for Everybody Specialization (Coursera) Documentation Official Python Documentation Python Tutorial YouTube Channels Corey Schafer freeCodeCamp Programming with Mosh Tech With Tim Bro Code CS Dojo Blogs Real Python Towards Data Science GeeksforGeeks Python Software Foundation Blog Communities Python Discord Reddit (r/Python) Stack Overflow GitHub Practice Websites LeetCode HackerRank Exercism Codewars CodingBat 6. Practice Projects Beginner Calculator To-Do List Quiz Game Password Generator Unit Converter Skills: Variables, loops, functions Intermediate Expense Tracker Contact Book Weather App Library System File Organizer Skills: Files, APIs, OOP Advanced Chat Application Flask Blog Web Scraper Automation Suite AI Chatbot Skills: Architecture, APIs, databases 7. Common Mistakes Copying code without understanding it Skipping practice Ignoring debugging Not reading error messages Learning too many libraries too early Avoiding projects Not using Git Giving up after difficult bugs 8. Milestones After Week 1 Write simple programs Understand variables and data types After Week 2 Build interactive console applications Use loops and conditions confidently After Week 3 Write reusable functions Work with lists and dictionaries After Week 4 Read/write files Handle exceptions After Week 8 Automate repetitive tasks Use APIs and external libraries After Week 12 Build complete Python applications independently Publish projects on GitHub 9. Assessment Weekly Quiz 10–20 conceptual questions 5 coding exercises Practical Challenges Reverse a string Build a calculator Parse a CSV file Consume an API Create a CRUD application Self-Check Questions Can I explain every line of my code? Can I solve the problem without a tutorial? Can I debug errors independently? Have I documented my project? Can someone else understand my code? 10. Portfolio Ideas Create and publish: Expense Tracker Weather Dashboard Password Manager To-Do Application File Organizer REST API Client Inventory Manager Flask Web Application Data Visualization Dashboard Automation Toolkit Include clear README files, screenshots, installation instructions, and example usage for each project. 11. Career Applications Job Roles Python Developer Backend Developer Data Analyst Data Scientist Machine Learning Engineer Automation Engineer QA Automation Engineer DevOps Engineer Cybersecurity Analyst Software Engineer Freelance Opportunities Automation scripts Web scraping API integrations Data processing Custom desktop tools Bot development Backend services Business Opportunities SaaS products Automation services AI-powered applications Data analytics consulting Custom software development Educational tools Certifications PCEP – Certified Entry-Level Python Programmer PCAP – Certified Associate in Python Programming Python Institute Certifications Google IT Automation with Python Professional Certificate 12. Advanced Learning Path After mastering Python fundamentals, specialize in one or more areas: Web Development: Flask, Django, FastAPI, SQL, Docker, REST APIs Data Science: NumPy, Pandas, Matplotlib, Seaborn, Jupyter Machine Learning & AI: Scikit-learn, TensorFlow, PyTorch, Hugging Face Automation: Selenium, Playwright, PyAutoGUI, scripting Cybersecurity: Network programming, penetration testing, security automation Cloud & DevOps: Docker, Kubernetes, AWS, Azure, CI/CD Game Development: Pygame, Arcade Desktop Applications: Tkinter, PySide, Kivy Final Goal By the end of this 90-day plan, you should have: A solid understanding of Python fundamentals. At least 8–10 completed projects in a GitHub portfolio. Experience using Git, APIs, databases, and testing. A clear specialization path based on your interests and career goals. The confidence to build real-world Python applications independently and continue advancing into professional software development or related fields.