PYTHON

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1. Module 1: Introduction to Python

1. 1.1. What is Python? - History and evolution of Python - Purpose and applications of Python 1.2. Setting up the Python Development Environment - Installing Python - Configuring Integrated Development Environments (IDEs) or text editors

1. Module 2: Python Basics

1. 2.1. Python Syntax and Structure - Variables, data types, and operators - Control flow (if statements, loops) 2.2. Functions and Methods - Defining and calling functions - Parameters and return values 2.3. Data Structures - Lists, tuples, and dictionaries - Working with sequences and mappings

1. Module 3: Object-Oriented Programming in Python

1. 3.1. Introduction to Object-Oriented Programming (OOP) - Classes and objects - Inheritance and polymorphism 3.2. Advanced OOP Concepts - Encapsulation, abstraction, and inheritance - Method overriding and overloading

1. Module 4: Exception Handling

1. 4.1. Handling Errors and Exceptions - Try-except blocks - Custom exceptions

1. Module 5: File Handling and Input/Output (I/O)

1. 5.1. Reading and Writing Files - Working with text and binary files - File I/O operations

1. Module 6: Python Modules and Libraries

1. 6.1. Standard Library - Exploring Python's built-in modules - Commonly used modules (e.g., os, datetime) 6.2. External Libraries - Installing and using third-party libraries (e.g., NumPy, pandas)

1. Module 7: Functional Programming in Python

1. 7.1. Lambda Functions - Anonymous functions in Python - Use cases and examples 7.2. Map, Filter, and Reduce - Functional programming with these higher-order functions

1. Module 8: Python Decorators and Generators

1. 8.1. Decorators - Creating and using decorators - Function and class decorators 8.2. Generators - Creating and using generator functions - Lazy evaluation

1. Module 9: Python for Data Science

1. 9.1. Data Analysis with Pandas - Data manipulation and analysis using Pandas - Reading and writing data 9.2. Data Visualization with Matplotlib and Seaborn - Creating plots and charts - Data visualization best practices

1. Module 10: Web Development with Python

1. 10.1. Web Frameworks (e.g., Django or Flask) - Building web applications with Python - Routing, views, and templates 10.2. RESTful API Development - Creating RESTful APIs using Python - Consuming APIs in Python

1. Module 11: Database Access with Python

1. 11.1. SQL and Relational Databases - Connecting to databases - CRUD operations with Python and SQL 11.2. NoSQL Databases - Working with document-based and key-value stores (e.g., MongoDB)

1. Module 12: Unit Testing in Python

1. 12.1. Writing Unit Tests - Unit testing basics - Testing frameworks (e.g., unittest, pytest)

1. Module 13: Python Best Practices and Code Quality

1. 13.1. Code Quality and Code Review - Writing clean and maintainable code - Code reviews and best practices

1. Module 14: Final Project

1. 14.1. Capstone Project - Students work on a real-world Python project, applying their knowledge to solve a practical problem. 14.2. Project Presentation - Students present their projects to the class, showcasing their Python skills and project outcomes. This comprehensive Python course provides students with a strong foundation in the Python programming language, object-oriented and functional programming principles, and practical application development. It includes hands-on coding exercises, a capstone project, and discussions about best practices in Python development. Additional resources, practical examples, and real-world applications are essential for students to become proficient Python developers.
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