- What is programming?
- History of Python.
- Setting up the development environment.
- IDLE.
- Jupyter Notebook.
- VS Code.
- Writing and running your first Python program.
Basic Syntax
- Comments.
- Indentation.
- Printing to the console.
Variables and Data Types
- Numbers (integers, floats).
- Strings.
- Booleans.
Basic Operators
- Numbers (integers, floats).
- Strings.
- Booleans.
Control Flow
- Conditional statements (if, elif, else).
- Loops (for loops, while loops).
- Break, continue, and pass statements.
Functions
- Defining and calling functions: Function arguments and return values.
- Scope and lifetime of variables in Lambda functions.
Data Structures: Lists
- Creating and accessing lists.
- List operations (indexing, slicing, adding, removing elements).
- List methods.
- append.
- extend.
- insert.
- remove.
- pop.
- clear.
- index.
- count.
- sort.
- Reverse.
Data Structures: Tuples and Sets
- Creating and accessing tuples.
- Tuple methods.
- Creating and accessing sets.
- Set operations.
- union.
- intersection.
- Difference.
Data Structures: Dictionaries
- Creating, accessing, and modifying dictionaries: Dictionary methods.
- keys.
- values.
- items.
- get.
- pop.
- update.
Working with Strings
- String operations.
- concatenation.
- slicing.
- formatting.
- String methods.
- find.
- replace.
- split.
- join.
- lower.
- upper.
- Strip.
File Handling
- Reading from files.
- Writing to files.
- Working with CSV files using the csv module.
Modules and Packages
- Importing modules.
- Standard library overview.
- Math.
- Datetime.
- Random.
- Installing and using third-party packages (pip).
Error Handling
- Understanding exceptions.
- Try, except, else, finally blocks.
- Raising exceptions.
Object-Oriented Programming (OOP)
- Classes and objects.
- Attributes and methods.
- Inheritance.
- Polymorphism.
Comprehensions
- List comprehensions.
- Dictionary comprehensions.
- Set comprehensions.
Decorators and Generators
- Understanding and using decorators.
- Creating and using generators.
Regular Expressions
- Introduction to regular expressions.
- Using the re module for pattern matching.
Advanced Data Handling with Pandas
- Introduction to Pandas.
- DataFrames and Series.
- Reading from and writing to different file formats.
- CSV.
- Excel.
- JSON.
- Data cleaning and manipulation.
Data Visualization
- Introduction to Matplotlib and Seaborn.
- Plotting graphs and charts.
- Customizing plots.
Web Scraping
- Introduction to web scraping.
- Using BeautifulSoup and requests.
- Handling web scraping challenges.
- Pagination.
- Dynamic content.
APIs and Web Services
- Understanding APIs.
- Making HTTP requests using requests.
- Parsing JSON data.
Working with Databases
- Introduction to SQL and databases.
- Using SQLite with Python.
- Performing a CRUD operation.
Concurrency and Parallelism
- Understanding concurrency vs. parallelism.
- Using the threading and multiprocessing modules.
Testing and Debugging
- Writing unit tests with unittest and pytest.
- Debugging techniques and tools.
Advanced OOP Concepts
- Abstract classes and interfaces.
- Design patterns.
- Metaclasses.
Advanced Python Libraries
- Introduction to NumPy for numerical computing.
- SciPy for scientific computing.
- Exploring additional libraries as per interest.
- TensorFlow for machine learning.
