Complete Python Programming Syllabus (Beginner to Advanced)
Python is one of the most versatile and beginner-friendly programming languages in the world. From web development and automation to data science and AI, Python forms the backbone of modern software development. This syllabus is designed as a structured learning roadmap, not just a list of topics. It focuses on building strong fundamentals, clear thinking, and professional-level coding skills. This guide covers: Python fundamentals from scratch Core programming concepts Advanced Python features Career-oriented applications Interview and professional preparation Beginner Level — Python Foundations 1. Introduction to Python What is Python History and features of Python Applications of Python Python vs other languages Installing Python Python versions Running Python programs Python interactive shell Writing your first Python program 2. Python Basics & Syntax Python keywords Identifiers Indentation and code structure Comments (single-line and multi-line) Variables and naming conventions Data types overview Type checking using type() Type conversion 3. Input, Output & Operators Input using input() Output using print() Formatted output Arithmetic operators Relational operators Logical operators Assignment operators Operator precedence 4. Control Flow Conditional Statements if if-else elif Nested conditions Looping Statements for loop while loop Loop Control break continue pass Intermediate Level — Core Python Concepts 5. Strings String creation Indexing and slicing String methods String formatting Escape characters Immutability String operations 6. Lists Creating lists Indexing and slicing List methods Nested lists Iterating through lists List comprehensions 7. Tuples Creating tuples Tuple operations Tuple unpacking Difference between list and tuple Use cases 8. Sets Set creation Set methods Set operations Difference between set and list Use cases 9. Dictionaries Dictionary creation Accessing elements Dictionary methods Iterating dictionaries Nested dictionaries Real-world use cases 10. Functions Defining functions Function parameters Return values Default arguments Keyword arguments Variable-length arguments (*args, **kwargs) Scope (local and global) Lambda functions 11. Modules & Packages Importing modules Built-in modules Creating custom modules Python packages __name__ == "__main__" Virtual environments Advanced Level — Professional Python 12. File Handling Reading files Writing files File modes Working with CSV files JSON handling Context managers using with 13. Exception Handling Types of errors try and except else and finally Multiple exceptions Custom exceptions Debugging techniques 14. Object-Oriented Programming (OOP) Classes and objects Constructors Instance and class variables Methods Encapsulation Inheritance Polymorphism Abstraction Magic methods (__str__, __len__, etc.) 15. Advanced Python Concepts List, set, and dictionary comprehensions Iterators and generators Decorators Closures Shallow vs deep copy Memory management Garbage collection 16. Python Standard Library math random datetime collections itertools functools os sys 17. Testing & Debugging Assertions Unit testing Writing test cases Testing frameworks overview Debugging tools Logging Specialized & Career-Oriented Topics 18. Data Structures & Algorithms with Python Time and space complexity Arrays and strings Stacks and queues Linked lists Trees Graphs Dynamic programming Greedy algorithms Recursion and backtracking 19. Automation & Scripting File and folder automation Web scraping basics Task scheduling Command-line tools Automation projects 20. Python for Web Development Backend fundamentals REST APIs JSON and HTTP Web frameworks overview Request–response cycle 21. Python for Data & AI NumPy basics Pandas basics Data cleaning Basic data visualization Working with datasets 22. Performance & Optimization Code optimization Profiling Efficient data handling Best practices PEP 8 guidelines Type hints 23. Real-World Projects Beginner mini projects Automation projects API-based projects Data-driven projects End-to-end Python applications 24. Interview & Professional Topics Common Python interview questions DSA problem solving Design patterns Code optimization Packaging and distribution Resume and project preparation 25. Python Programming Playlist --- More structured Python learning guides and hands-on roadmaps coming soon.