This collection of notes provides a comprehensive guide to understanding Python, with a focus on practical application and progressive skill development.
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- What is Python?
- Installation and setup
- Python interpreter and first program
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- Variables and basic types
- Operators and expressions
- Input/output operations
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- Conditional statements
- Loops and iterations
- Control flow tools
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- Lists, tuples, sets, and dict
- Comprehensions
- Overview of Python's Built-in Data Structures
- Collections Module
- Choosing the Right Data Structure
- Comprehensions
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Functions ⚙️
- Defining and calling functions
- Parameters and return values
- Lambda functions and closures
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- Creating modules
- Importing and using modules
- Package structure and management
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- Classes and objects
- Inheritance and polymorphism
- Encapsulation and abstraction
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- Reading and writing files
- Working with paths and directories
- Serialization
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- Exception handling
- Custom exceptions
- Debugging techniques
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- Decorators
- Generators and iterators
- Context managers
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- Threading
- Multiprocessing
- Async programming
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- Unit testing
- Documentation standards
- Testing best practices
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- NumPy and Pandas fundamentals
- Data manipulation
- Visualization basics
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Project Example: NumPy Image Filter App 🖼️
- Practical application of NumPy
- Interactive web app with Streamlit
- Image processing basics
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Project Example: Pandas Candlestick Analysis 📈
- Financial data analysis with Pandas
- Time-series data processing
- Interactive financial dashboards
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- Lightweight web application development
- Routing and request handling
- Templates and application structure
- Sub-topics:
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Flask-SocketIO: Real-time Web Applications 🔌
- WebSocket integration with Flask
- Real-time bidirectional communication
- Building interactive dashboards
- Sub-topics:
(These notes are designed for beginners to intermediate Python developers and assume basic programming knowledge. Each topic builds on the previous ones, creating a comprehensive learning journey.)