Presentation1

1. Introduction to Python

  • What is Python?
  • Installing Python and setting up a development environment (IDEs: Jupyter, VS Code, PyCharm)
  • Running Python code (script vs. interactive mode)
  • Python syntax and basic commands

2. Data Types and Variables

  • Numeric data types: integers, floats
  • Strings and string manipulation
  • Boolean values
  • Lists, tuples, and sets
  • Dictionaries
  • Type casting and checking types

3. Control Flow

  • Conditional statements (if, else, elif)
  • Loops: for and while
  • Nested loops
  • break, continue, and pass statements

4. Functions

  • Defining functions
  • Function arguments and parameters (positional, keyword, default)
  • Return values
  • *args and **kwargs
  • Lambda functions
  • Scope (global vs local variables)

5. Input and Output

  • Taking user input
  • Printing output
  • File I/O (reading from and writing to files)

6. Error and Exception Handling

  • Common Python errors
  • Using try, except, finally, and else
  • Raising exceptions

7. Data Structures

  • Lists: operations, slicing, and methods
  • Tuples: immutability and use cases
  • Sets: uniqueness, set operations (union, intersection)
  • Dictionaries: key-value pairs, common methods
  • Comprehensions (list, set, and dictionary comprehensions)

8. Modules and Packages

  • Importing built-in modules
  • Creating and importing custom modules
  • Installing external packages (using pip)
  • Understanding and managing virtual environments

9. Object-Oriented Programming (OOP)

  • Classes and objects
  • Attributes and methods
  • The __init__ method (constructor)
  • Inheritance
  • Polymorphism
  • Encapsulation
  • Magic methods (e.g., __str__, __len__, etc.)

10. Working with Libraries

  • Using libraries such as:
    • math (for mathematical operations)
    • random (for generating random values)
    • datetime (working with dates and times)
    • os and sys (for file system and system operations)
    • json (working with JSON data)
    • collections (defaultdict, namedtuple, Counter, deque)

11. Data Science and Visualization (optional for advanced courses)

  • Using pandas for data manipulation
  • Using numpy for numerical computations
  • Data visualization with matplotlib and seaborn

12. Testing and Debugging

  • Using print statements and logging
  • Introduction to debugging tools (e.g., pdb)
  • Writing unit tests with unittest or pytest

13. Working with APIs

  • Making HTTP requests with requests
  • Parsing and handling JSON
  • Understanding REST APIs and interacting with them

14. File Handling

  • Reading and writing text files
  • Working with CSV, JSON, and Excel files
  • File paths and directories

15. Regular Expressions (Regex)

  • Introduction to regex
  • Matching patterns in strings
  • Using the re module

16. Concurrency and Parallelism (Advanced)

  • Multithreading
  • Multiprocessing
  • Using async and await for asynchronous programming

17. Database Interaction

  • Introduction to SQLite
  • CRUD operations using Python
  • Using sqlite3 or SQLAlchemy for database interaction

18. Web Development (optional)

  • Introduction to Flask or Django
  • Building simple web applications
  • Handling requests and responses

19. Version Control and Collaboration

  • Introduction to Git
  • Using Git for version control with Python projects
  • Collaborating with GitHub

20. Best Practices

  • Writing clean and readable code (PEP 8 standards)
  • Code documentation
  • Refactoring code
  • Writing efficient and optimized code

21. Advanced Topics (optional)

  • Decorators
  • Generators and iterators
  • Context managers (with with statement)
  • Metaprogramming and introspection
  • Type hinting and annotations