Course Overview
Python Programming: Basic to Advanced is a comprehensive instructor-led training program designed for developers, software engineers, automation professionals, data analysts, and IT professionals who want to build a strong foundation in Python and advance to professional software development practices. The course covers Python fundamentals, object-oriented programming, modular application development, modern package management, testing, concurrency, performance optimization, and deployment best practices using the latest Python ecosystem.
Participants begin with Python language fundamentals including variables, operators, control structures, functions, collections, file handling, and modules before progressing to advanced concepts such as decorators, generators, context managers, dataclasses, asynchronous programming, type hints, dependency management, testing, profiling, packaging, and documentation.
The training also introduces modern Python development workflows using virtual environments, uv package management, PEP standards, static type checking, version management, and production-ready coding practices. Through extensive hands-on exercises and real-world implementation scenarios, learners gain practical experience in building maintainable, scalable, and enterprise-grade Python applications.
Course Objective
Upon successful completion of this course, participants will be able to:
- Develop Python applications using modern programming practices and coding standards.
- Write clean, modular, reusable, and maintainable Python code.
- Work effectively with Python data structures, functions, modules, and packages.
- Implement object-oriented programming concepts using classes, inheritance, polymorphism, and abstraction.
- Manage Python environments and third-party dependencies using venv and uv.
- Perform file processing, data serialization, and regular expression-based text processing.
- Build robust applications with exception handling, logging, and debugging techniques.
- Develop asynchronous applications using asyncio and concurrency patterns.
- Create automated tests using unittest and pytest frameworks.
- Package, optimize, document, and deploy Python applications using modern development workflows.
Pre-requisites
Participants should have:
- Basic understanding of computer programming concepts.
- Familiarity with variables, loops, conditional statements, and functions.
- Basic knowledge of any programming language is beneficial but not mandatory.
- Understanding of operating system concepts and command-line usage is recommended.
- No prior Python programming experience is required.
Course Curriculum
- Introduction to Python
- Python Features and Applications
- Installing Python
- Python Interpreter
- Running Python Programs
- Python Syntax
- Variables and Data Types
- Input and Output Operations
- Comments and Documentation
- Built-in Functions
- Arithmetic Operators
- Comparison Operators
- Logical Operators
- Assignment Operators
- Membership Operators
- Identity Operators
- Conditional Statements
- if, elif and else
- while Loop
- for Loop
- break, continue and pass
- Loop else Clause
- Lists
- Tuples
- Dictionaries
- Sets
- Nested Collections
- List Comprehensions
- Dictionary Comprehensions
- Set Comprehensions
- Working with Complex Data Structures
- Common Collection Operations
- Defining Functions
- Parameters and Arguments
- Default Arguments
- Keyword Arguments
- Variable-Length Arguments
- Lambda Functions
- Recursive Functions
- Nested Functions
- Scope and Namespaces
- Global and Local Variables
- Documentation Strings
- File Handling
- Reading and Writing Files
- Text Files
- Binary Files
- pathlib Module
- JSON Processing
- CSV Processing
- Serialization
- Pickle Module
- Working with File Paths
- Import Statements
- Creating Modules
- Package Structure
- init.py
- Absolute and Relative Imports
- Module Search Path
- Standard Library Modules
- Reloading Modules
- Building Reusable Packages
- Virtual Environments
- Creating venv Environments
- Activating and Managing Environments
- pip Package Manager
- Installing and Upgrading Packages
- requirements.txt
- Introduction to pyproject.toml
- Dependency Management Best Practices
- Introduction to uv
- Installing uv
- Creating Virtual Environments with uv
- Package Installation and Removal
- Dependency Resolution
- Running Python Applications
- Managing Project Environments
- Comparing uv with pip and venv
- Classes and Objects
- Constructors
- Instance and Class Variables
- Instance, Class and Static Methods
- Inheritance
- Multiple Inheritance
- Polymorphism
- Encapsulation
- Abstraction
- Magic Methods
- Dataclasses
- Object-Oriented Design Principles
- Iterators
- Iterables
- Generator Functions
- Generator Expressions
- Decorators
- Closures
- Higher-Order Functions
- Functional Programming Concepts
- collections Module
- itertools Module
- String Operations
- String Formatting
- f-Strings
- Unicode and Encoding
- String Methods
- Regular Expressions
- Pattern Matching
- Search and Replace
- Text Processing
- Exception Hierarchy
- try, except, else and finally
- Raising Exceptions
- Custom Exceptions
- Exception Chaining
- Context Managers
- with Statement
- contextlib Module
- Logging Module
- Debugging Best Practices
- Introduction to asyncio
- Coroutines
- async and await
- Event Loop
- Tasks
- gather()
- Concurrent Programming
- Threading vs Async Programming
- High-Level Multiprocessing Concepts
- unittest Framework
- pytest Overview
- Test Cases
- Assertions
- Fixtures
- Test-Driven Development
- Docstrings
- Type Hints
- Static Type Checking
- PEP 8
- PEP 20
- PEP 257
- Code Formatting Tools
- Performance Measurement
- timeit Module
- cProfile
- Memory Optimization
- Efficient Data Structures
- Algorithm Performance
- Optimizing Loops
- Performance Best Practices
- HTTP Requests
- requests Library
- urllib
- Web Scraping Fundamentals
- Beautiful Soup
- lxml
- Selenium Overview
- Scrapy Overview
- Processing HTML Data
- JSON APIs
- Python Packaging
- pyproject.toml
- Building Packages
- Python Wheels
- Versioning
- Publishing Packages
- Installing Custom Packages
- Distribution Best Practices
- Latest Python Features
- Python Release Cycle
- New Language Enhancements
- Deprecations and Migration
- SOLID Principles
- Clean Code Practices
- Project Structure
- Enterprise Python Development
- Production Deployment Considerations
- Capstone Project and Course Wrap-up
