Python Programming

Course Duration: 24-32 Weeks

Target Audience: Students, Software Developers, Data Scientists, AI Enthusiasts

Prerequisites: Basic Computer Knowledge

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Module 1: Introduction to Python

• Overview of Python and Its Features
• History and Evolution of Python
• Installing Python (Windows, macOS, Linux)
• Setting Up Python Environment (IDLE, Jupyter Notebook, PyCharm, VS Code)
• Running Python Scripts and Interactive Mode
• Python Syntax and Code Structure

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Module 2: Python Basics – Data Types and Operators

• Variables and Data Types (int, float, string, list, tuple, dictionary, set)
• Type Conversion and Type Casting
• Operators in Python (Arithmetic, Relational, Logical, Bitwise, Assignment, Membership)
• String Manipulation and Formatting
• Basic Input and Output Operations (print(), input())

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Module 3: Control Flow Statements

• Conditional Statements (if, elif, else)
• Looping Constructs (for, while, break, continue)
• Nested Loops and Conditional Statements
• Iterating Over Data Structures (Lists, Tuples, Dictionaries, Sets)

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Module 4: Functions and Modules

• Defining and Calling Functions
• Function Arguments and Return Values
• Lambda Functions (Anonymous Functions)
• Recursive Functions
• Python Modules and Packages
• Importing Modules (math, random, datetime, os, sys)
• Creating and Using Custom Modules

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Module 5: Object-Oriented Programming (OOP) in Python

• Understanding Classes and Objects
• Creating and Using Classes and Objects
• Class Variables and Instance Variables
• Encapsulation, Inheritance, and Polymorphism
• Abstract Classes and Interfaces
• Magic Methods (__init__, __str__, __len__, __getitem__)

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Module 6: Exception Handling and Debugging

• Understanding Errors and Exceptions
• Handling Exceptions (try, except, finally, raise)
• Built-in Exceptions (TypeError, ValueError, KeyError, IndexError)
• Debugging Techniques (print(), assert, logging, pdb)

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Module 7: Working with Files and Directories

• File Handling Basics (open(), read(), write(), close())
• Reading and Writing Files (Text, Binary, CSV, JSON)
• File Operations (rename, remove, mkdir, rmdir)
• Working with OS and SYS Modules

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Module 8: Data Structures in Python

• Lists (Indexing, Slicing, Methods, List Comprehension)
• Tuples and Sets (Immutable vs Mutable)
• Dictionaries (Keys, Values, Methods)
• Stacks, Queues, and Linked Lists (Using Lists and Collections)
• Working with Collections Module (deque, Counter, defaultdict)

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Module 9: Regular Expressions and String Manipulation

• Understanding Regular Expressions (RegEx)
• Using re Module for Pattern Matching
• Searching, Replacing, and Extracting Data
• Handling String Formatting and Manipulation

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Module 10: Working with Databases (SQL & NoSQL)

• Introduction to Databases and SQL
• Connecting Python with MySQL and PostgreSQL
• Performing CRUD Operations with SQL Databases
• Introduction to NoSQL Databases (MongoDB)
• Using Python with MongoDB (PyMongo)

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Module 11: Web Scraping with Python

• Introduction to Web Scraping
• Fetching Data with Requests Module
• Parsing HTML with BeautifulSoup
• Extracting Data from Websites
• Automating Web Scraping with Selenium

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Module 12: Working with APIs in Python

• What are APIs?
• Understanding RESTful APIs
• Making API Calls with Requests Module
• Handling JSON and XML Responses
• Consuming Third-Party APIs (Weather API, Twitter API)

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Module 13: Data Science and Machine Learning with Python

• Introduction to Data Science
• Working with NumPy and Pandas for Data Manipulation
• Data Visualization with Matplotlib and Seaborn
• Introduction to Machine Learning with Scikit-Learn
• Building Basic ML Models (Linear Regression, Decision Trees)

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Module 14: GUI Programming with Python

• Introduction to GUI Development
• Using Tkinter for GUI Applications
• Creating Forms, Buttons, and Input Fields
• Event Handling in GUI Applications
• Working with PyQt and Kivy for Advanced GUI

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Module 15: Web Development with Flask and Django

• Introduction to Web Frameworks
• Setting Up Flask and Django
• Creating Routes and Views
• Handling Forms and Templates
• Connecting Web Apps with Databases
• Deploying Python Web Applications

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Module 16: Automation and Scripting in Python

• Writing Python Scripts for Automation
• Automating File and Folder Operations
• Sending Emails Using Python
• Automating Web Interactions with Selenium
• Working with Scheduling Tasks (Cron Jobs, Task Scheduler)

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Module 17: Networking and Cybersecurity with Python

• Working with Sockets and Networking in Python
• Creating Simple Chat Applications
• Using Python for Cybersecurity (Penetration Testing Basics)
• Introduction to Cryptography and Hashing

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Module 18: Multi-Threading and Parallel Computing

• Understanding Multi-Threading in Python
• Using threading and multiprocessing Modules
• Asynchronous Programming with AsyncIO

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Module 19: Cloud Computing and Python

• Using Python for Cloud Computing
• Working with AWS (Boto3)
• Deploying Python Apps on Cloud Platforms

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Module 20: Game Development with Python

• Introduction to Game Development
• Working with Pygame Library
• Creating Simple Games and Animations

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Module 21: Python for IoT (Internet of Things)

• Using Python with Raspberry Pi
• Connecting Sensors and Devices
• Data Collection and Processing

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Module 22: Version Control and Collaboration with Git

• Understanding Git and GitHub
• Using Git Commands (clone, commit, push, pull)
• Collaborating on Open Source Projects

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Module 23: Deployment and Packaging Python Applications

• Creating Python Executable Files (pyinstaller)
• Packaging Python Projects with Pip and Virtual Environments
• Deploying Applications on Heroku, AWS, and Docker

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Module 24: Advanced Topics and Real-World Projects

• Design Patterns in Python
• Writing Efficient and Optimized Python Code
• Working on Real-World Projects
• Best Practices for Writing Clean and Maintainable Python Code