Python Programming – Complete Course with Practical Examples — Working with Strings in Depth

Getting Started with Python and the Course

• Course Overview and Learning Path
• What is Python and Where is it Used?
• Install and Setup Python
• Setup Python IDE
• Create Virtual Environment
• Running Your First Python Program
• How Python Executes Code
• Install Jupyter Notebooks

Python Syntax, Indentation, and Core Concepts

• Python Syntax Rules and Style (PEP 8)
• Indentation and Code Blocks
• Statements, Expressions, and Comments

Variables, Data Types, and Type Conversion

• Declaring and Using Variables
• Numbers, Booleans, and None
• Strings: Basics and Common Operations
• Collection Data Types
• Type Conversion and Casting
• Dynamic Typing and Variable Scope Basics
• Quiz - Variables, Data Types, and Type Conversion

Operators, Expressions, and Control Flow

• Arithmetic, Comparison, and Logical Operators
• Assignment, Identity, and Membership Operators
• Operator Precedence and Chaining
• Writing Conditional Logic with if, elif, else
• Nested Conditionals and Ternary Expressions
• Quiz - Operators, Expressions, and Control Flow

Loops and Iteration Patterns

• for Loops and Iterating Over Sequences
• while Loops and Loop Control Statements
• break, continue, and else with Loops
• Common Loop Patterns and Idioms
• Nested Loops and Performance Considerations
• Quiz - Loops and Iteration Patterns

Working with Strings in Depth

• String Indexing, Slicing, and Immutability
• Essential String Methods (find, replace, split, join)
• Advanced String Formatting: f-strings and format()
• Working with Regular Expressions (Intro)
• Multi-line Strings and Handling Encoding
• Practical Text Processing Examples
• Quiz - Working with Strings in Depth

Collections: Lists, Tuples, Sets, and Dictionaries

• Lists: Creation, Indexing, and Slicing
• Modifying Lists and List Methods
• Tuples and When to Use Them
• Sets and Set Operations
• Dictionaries: Key-Value Storage
• Practical Data Structures Workshop
• Quiz - Collections: Lists, Tuples, Sets, and Dictionaries

Functions and Program Structuring

• Defining and Calling Functions
• Function Parameters and Return Values
• Default, Keyword, and Positional Arguments
• *args, **kwargs, and Flexible Interfaces
• Docstrings and Writing Self-Documenting Functions
• Practical Function Design Exercises
• Quiz - Functions and Program Structuring

Functional Programming Concepts in Python

• First-Class Functions and Higher-Order Functions
• Lambda Expressions and Inline Functions
• map, filter, and reduce
• List, Set, and Dict Comprehensions
• Immutability, Pure Functions, and Side Effects
• Case Study: Data Transformation Pipelines
• Quiz - Functional Programming Concepts in Python

Modules, Packages, and Code Organization

Error Handling and Debugging Fundamentals

• Common Error Types and Tracebacks
• Exception Handling with try, except, else, finally
• Raising Exceptions and Creating Custom Exceptions
• Debugging Techniques and Using pdb / IDE Debuggers
• Logging Basics for Python Applications
• Practical Debugging Scenarios
• Quiz - Error Handling and Debugging Fundamentals

File Handling and Data Formats

• Reading and Writing Text Files Safely
• Working with CSV Files Using csv Module
• Reading and Writing JSON Data
• Path Handling with pathlib and os
• Context Managers and the with Statement
• Mini Project: Simple Data Import/Export Utility
• Quiz - File Handling and Data Formats

Object-Oriented Programming in Python

• Classes, Objects, and Attributes
• Methods, self, and Class vs Instance Data
• Encapsulation, Properties, and Private Conventions
• Inheritance, Composition, and Method Overriding
• Special Methods and Operator Overloading
• OOP Case Study: Building a Simple Domain Model

Advanced Python: Iterators, Generators, and Decorators

• Iteration Protocol and Custom Iterators
• Generators and yield for Lazy Evaluation
• Generator Expressions and Pipelines
• Decorators: Functions that Modify Functions
• Writing Reusable Decorators (Logging, Timing, Caching)
• Real-World Patterns with Iterators and Decorators

Python Standard Library for Real-World Tasks

• Working with dates and times (datetime)
• Collections, itertools, and functools
• Handling files and directories (os, shutil, pathlib)
• Data Serialization (json, pickle)
• Subprocesses and System Interaction
• Practical Utilities: Building Handy CLI Tools

Python for Automation and Scripting

• Command-Line Scripts and Argument Parsing
• Automating File and Folder Operations
• Scheduling and Running Repetitive Tasks
• Automating Reports and Notifications (Email, PDFs)
• Automation Mini Project: Personal Productivity Tool

Testing and Quality Assurance in Python

• Why Testing Matters: Types of Tests
• Writing Unit Tests with unittest and/or pytest
• Assertions, Fixtures, and Test Organization
• Test-Driven Development (TDD) Basics
• Measuring Coverage and Maintaining Test Suites
• Refactoring Code Safely with Tests