Python Training Course (Scratch to Advanced)

30 Hours

- Beginners looking to start programming with Python
- Software Developers and Engineers
- Data Scientists and Analysts
- Web Developers and Automation Engineers
- Anyone interested in learning Python from basics to advanced applications

Module 1: Introduction to Python
 Why Python?
 Installing Python and Setting Up IDE
 Understanding Python Interpreters
 First Python Program
Module 2: Python Basics
 Variables, Data Types, and Operators
 Input/Output Functions
 Basic String Operations
 Control Flow: if, elif, else
Module 3: Loops and Iterations
 for and while Loops
 Break and Continue Statements
 Loop Else Clauses
 Nested Loops
Module 4: Functions in Python
 Defining and Calling Functions
 Function Arguments (Default, Keyword, *args, **kwargs)
 Lambda Functions
 Recursion
Module 5: Data Structures
 Lists, Tuples, Sets, and Dictionaries

 Comprehensions (List, Dict, Set)
 Nested Data Structures
 Built-in Functions and Methods
Module 6: Modules and Packages
 Importing Standard Modules
 Creating Custom Modules
 Using pip and Virtual Environments
 Working with External Libraries
Module 7: File Handling
 Reading and Writing Files
 Working with CSV, JSON Files
 Context Managers and File Exceptions
Module 8: Object-Oriented Programming
 Classes and Objects
 Constructors and Destructors
 Inheritance and Polymorphism
 Encapsulation and Abstraction
Module 9: Error Handling
 Try, Except, Else, Finally
 Raising Exceptions
 Creating Custom Exceptions
Module 10: Advanced Python Concepts
 Decorators and Generators
 Iterators and Context Managers
 Multithreading and Multiprocessing
 Regular Expressions
Module 11: Working with Databases
 Connecting to SQLite and MySQL
 CRUD Operations
 Using ORM (like SQLAlchemy) Basics
Module 12: Introduction to Web and APIs
 Using Flask for Web Development
 Creating REST APIs
 Consuming APIs with Requests Module
Module 13: Introduction to Data Analysis

 Working with NumPy and Pandas
 Data Cleaning and Transformation
 Basic Data Visualization with Matplotlib and Seaborn
Module 14: Final Project and Best Practices
 Building a Mini Project
 Code Quality and PEP8
 Debugging and Logging
 Version Control with Git