Python for Beginners – List of Topics

 Here’s a comprehensive list of topics to learn Python programming for beginners. This roadmap will help you systematically build your skills and progress from basic concepts to more advanced topics:

1. Introduction to Python

• What is Python?
• Installing Python and setting up the environment
• Running Python code (using the terminal, IDEs like VSCode, PyCharm)
• Introduction to the Python interpreter (Interactive Mode)

2. Python Syntax and Structure

• Writing and running Python scripts
• Indentation and the importance of whitespace
• Python comments (single-line and multi-line)
• Understanding the Python execution model

3. Variables and Data Types

• Variables in Python (naming conventions)
• Primitive Data Types:
  • Strings
  • Integers
  • Floats
  • Booleans
• Type conversion (casting)
• Understanding immutability vs mutability

4. Basic Input and Output

• input() function for user input
• print() function for displaying output
• String formatting (using f-strings, .format(), concatenation)

5. Operators

• Arithmetic operators (+, -, *, /, %, //, **)
• Comparison operators (==, !=, >, <, >=, <=)
• Logical operators (and, or, not)
• Assignment operators (=, +=, -=, etc.)
• Membership and Identity operators (in, not in, is, is not)

6. Control Flow Statements

• Conditional statements: if, elif, else
• Nested conditions
• Boolean expressions
• The pass statement

7. Loops

• for loop
  • Iterating over a range of numbers using range()
  • Iterating over lists, tuples, dictionaries, and strings
• while loop
• break, continue, and else in loops
• Nested loops

8. Functions

• Defining functions using def
• Function parameters and return values
• Default parameters
• Keyword arguments
• Variable-length arguments (*args, **kwargs)
• Scope and Lifetime (Local vs Global variables)
• Lambda functions (anonymous functions)

9. Data Structures in Python

• Lists:
  • Creating and accessing lists
  • List operations (indexing, slicing, append, remove, pop)
  • List comprehension
• Tuples:
  • Creating and accessing tuples
  • Immutable nature of tuples
• Dictionaries:
  • Key-value pairs, creating and accessing dictionaries
  • Dictionary methods (keys(), values(), items())
  • Iterating over dictionaries
• Sets:
  • Creating sets
  • Set operations (union, intersection, difference)
• Strings:
  • String manipulation (slicing, concatenation, repetition)
  • String methods (e.g., .lower(), .upper(), .replace())

10. Error Handling and Exceptions

• Try-except blocks for error handling
• else and finally blocks
• Raising exceptions with raise
• Common exceptions (ValueError, TypeError, etc.)
• Custom exceptions

11. File Handling

• Reading files (open(), read(), readlines())
• Writing to files (write(), writelines())
• Closing files (close())
• Working with file paths and directories
• Using context managers (with statement)

12. Modules and Libraries

• Importing built-in Python libraries (e.g., math, random, os)
• Creating and importing custom modules
• Exploring Python’s standard library
• Installing third-party libraries using pip

13. Object-Oriented Programming (OOP) Basics

• Defining classes and objects
• Instance variables and methods
• Constructors (__init__ method)
• Inheritance
• Polymorphism
• Encapsulation
• Abstraction
• self keyword

14. Basic Debugging Techniques

• Using print() for debugging
• Debugging with IDEs (breakpoints, stepping through code)
• Understanding stack traces

15. Working with Libraries and Packages

• Installing and managing packages using pip
• Introduction to popular Python libraries:
  • numpy for numerical computation
  • pandas for data manipulation
  • matplotlib for plotting
  • requests for HTTP requests

16. Basic Algorithms and Problem Solving

• Sorting algorithms (e.g., bubble sort, selection sort)
• Searching algorithms (e.g., linear search, binary search)
• Simple mathematical problems (factorial, Fibonacci sequence)
• Introduction to time and space complexity

17. Introduction to Web Development with Python

• Overview of web frameworks like Flask and Django
• Creating a simple web application with Flask
• Understanding HTTP methods (GET, POST)
• Using templates and rendering HTML

18. Basic Data Analysis and Visualization

• Introduction to data analysis with pandas
• Working with data structures in pandas (DataFrames, Series)
• Basic plotting with matplotlib
• Introduction to numpy for handling numerical data

19. Introduction to Testing

• Writing basic tests using the unittest module
• Assertions and test cases
• Running tests and interpreting results

20. Working with APIs

• Introduction to RESTful APIs
• Sending HTTP requests with requests library
• Handling JSON data
• Interacting with public APIs (e.g., OpenWeatherMap, Twitter)