Python course

Beginner Level:
1. Introduction to Python:
* What is Python? Why is it popular?
* Installing Python and setting up an IDE (like VS Code or Jupyter Notebooks).
2. Basic Syntax:
* Variables, data types (int, float, string, etc.), and basic operators.
* Simple input/output with input() and print().
3. Control Flow:
* Conditional statements: if, elif, else.
* Loops: for and while.
4. Functions:
* Creating and calling functions.
* Understanding function arguments and return values.
5. Data Structures:
* Lists, Tuples, Sets, Dictionaries.
* How to access, modify, and loop through these data structures.
6. Error Handling:
* Understanding try, except, and catching errors.
7. Modules and Libraries:
* Importing and using built-in Python modules.
* Introduction to libraries like math, random, and datetime.

Intermediate Level:
1. Object-Oriented Programming (OOP):
* Classes, Objects, Methods, and Attributes.
* Inheritance, Polymorphism, Encapsulation.
2. File Handling:
* Reading from and writing to text files.
* Working with CSV and JSON files.
3. Comprehensions:
* List, set, and dictionary comprehensions for more concise code.
4. Regular Expressions (Regex):
* Pattern matching and extracting data from strings.
5. Libraries for Data Science:
* Introduction to NumPy, Pandas, and Matplotlib.

Advanced Level:
1. Decorators and Generators:
* Creating and using decorators.
* Writing and understanding generators.
2. Concurrency:
* Threads, asyncio, and multiprocessing.
3. Testing:
* Unit testing with unittest or pytest.
4. Advanced Libraries:
* Working with web frameworks (like Flask or Django).
* Using APIs (RESTful APIs, JSON parsing).Beginner Level:
1. Introduction to Python:
* What is Python? Why is it popular?
* Installing Python and setting up an IDE (like VS Code or Jupyter Notebooks).
2. Basic Syntax:
* Variables, data types (int, float, string, etc.), and basic operators.
* Simple input/output with input() and print().
3. Control Flow:
* Conditional statements: if, elif, else.
* Loops: for and while.
4. Functions:
* Creating and calling functions.
* Understanding function arguments and return values.
5. Data Structures:
* Lists, Tuples, Sets, Dictionaries.
* How to access, modify, and loop through these data structures.
6. Error Handling:
* Understanding try, except, and catching errors.
7. Modules and Libraries:
* Importing and using built-in Python modules.
* Introduction to libraries like math, random, and datetime.

Intermediate Level:
1. Object-Oriented Programming (OOP):
* Classes, Objects, Methods, and Attributes.
* Inheritance, Polymorphism, Encapsulation.
2. File Handling:
* Reading from and writing to text files.
* Working with CSV and JSON files.
3. Comprehensions:
* List, set, and dictionary comprehensions for more concise code.
4. Regular Expressions (Regex):
* Pattern matching and extracting data from strings.
5. Libraries for Data Science:
* Introduction to NumPy, Pandas, and Matplotlib.

Advanced Level:
1. Decorators and Generators:
* Creating and using decorators.
* Writing and understanding generators.
2. Concurrency:
* Threads, asyncio, and multiprocessing.
3. Testing:
* Unit testing with unittest or pytest.
4. Advanced Libraries:
* Working with web frameworks (like Flask or Django).
* Using APIs (RESTful APIs, JSON parsing).