Python

Module 1: Introduction to Python

• Overview of Python
  • History, features, and applications of Python
  • Installing Python and setting up development environment (IDE)

Module 2: Python Basics

• Syntax and Structure
  • Understanding Python syntax and code structure
  • Writing and executing Python scripts

Module 3: Variables, Data Types, and Operators

• Variables and Constants
  • Declaring variables and assigning values
  • Working with different data types: strings, numbers, lists, tuples, dictionaries
• Operators
  • Arithmetic, comparison, logical, and assignment operators

Module 4: Control Flow and Functions

• Control Flow
  • Conditional statements: if-elif-else, nested conditions
  • Looping structures: for loops, while loops
• Functions
  • Defining functions with parameters and return values
  • Lambda functions and function decorators

Module 5: Data Structures in Python

• Lists and Tuples
  • Operations, slicing, and manipulation
• Dictionaries
  • Creating dictionaries, accessing and modifying elements
• Sets
  • Operations and methods for set manipulation

Module 6: File Handling and Exception Handling

• File Handling
  • Reading from and writing to files using Python
  • Working with CSV and JSON files
• Exception Handling
  • Handling exceptions using try-except blocks
  • Raising and handling custom exceptions

Module 7: Object-Oriented Programming (OOP) in Python

• Classes and Objects
  • Defining classes and creating objects in Python
  • Constructors, instance variables, and methods
• Inheritance and Polymorphism
  • Implementing inheritance and method overriding
  • Polymorphism with method overloading and overriding

Module 8: Introduction to Python Libraries

• NumPy and Pandas
  • Introduction to data manipulation and analysis with NumPy and Pandas
• Matplotlib and Seaborn
  • Data visualization using Matplotlib and Seaborn for graphical representation

Module 9: Web Development with Python (Optional)

• Introduction to Flask/Django
  • Building web applications using Flask or Django frameworks
  • Handling HTTP requests and rendering HTML templates

Module 10: Data Science with Python (Optional)

• Introduction to Data Science Libraries
  • Using libraries like Scikit-learn for machine learning
  • Handling data with Pandas for data analysis tasks

Module 11: Project Work and Applications

• Real-World Projects
  • Applying Python skills to solve real-world problems
  • Developing applications or automating tasks

Course Duration

• Total Duration: 60 hours (adjustable based on the depth of coverage)
• Schedule: Flexible timing options available

Course Material

• Comprehensive course materials, including lecture notes and coding exercises
• Access to recorded sessions for review and practice
• Practical assignments and hands-on projects

Certification

• Upon successful completion, participants will receive a certificate of completion