Python Training: Unleash Your Potential with the Power of Programming

Introduction to Python

1. Python Overview
2. History of Python
3. Installing Python and Setting Up Environment
4. Writing and Executing Python Programs

Python Basics

1. Python Syntax and Semantics
2. Variables and Data Types
3. Basic Operators
4. Conditional Statements: if, if-else, if-elif-else
5. Loops: for, while

Data Structures in Python

1. Lists
2. Tuples
3. Sets
4. Dictionaries

Functions and Modules

1. Defining and Calling Functions
2. Function Arguments and Return Values
3. Lambda Functions
4. Modules and Packages
5. Importing and Using Standard Library Modules

File Handling

1. Reading and Writing Files
2. Working with CSV and JSON Files
3. File Handling Best Practices

Exception Handling

1. Understanding Exceptions
2. Try, Except, Else, and Finally Blocks
3. Custom Exceptions

Object-Oriented Programming (OOP)

1. Introduction to OOP Concepts
2. Classes and Objects
3. Constructors and Destructors
4. Inheritance
5. Polymorphism
6. Encapsulation and Abstraction

Advanced Python Concepts

1. List Comprehensions
2. Generators and Iterators
3. Decorators
4. Context Managers

Working with Libraries and Frameworks

1. NumPy for Numerical Computing
2. Pandas for Data Manipulation and Analysis
3. Matplotlib and Seaborn for Data Visualization
4. Requests for HTTP Requests

Web Development with Python

1. Introduction to Web Development Frameworks
2. Flask: Building a Simple Web Application
3. Django: Building a Full-Featured Web Application
4. Working with Templates and Forms in Flask and Django

Database Connectivity

1. Working with SQLite and SQLAlchemy
2. Connecting to MySQL and PostgreSQL Databases
3. Performing CRUD Operations

APIs and Web Scraping

1. Introduction to RESTful APIs
2. Consuming APIs with Requests
3. Web Scraping with Beautiful Soup and Scrapy

Data Science and Machine Learning

1. Introduction to Data Science with Python
2. Exploratory Data Analysis with Pandas
3. Machine Learning with Scikit-Learn
4. Building and Evaluating Machine Learning Models

Automation and Scripting

1. Writing Scripts for Automation
2. Automating Tasks with Python
3. Scheduling Scripts with Cron (Linux) or Task Scheduler (Windows)

Testing and Debugging

1. Introduction to Unit Testing
2. Writing Test Cases with unittest and pytest
3. Debugging Techniques and Tools

Version Control with Git

1. Introduction to Git and Version Control
2. Basic Git Commands
3. Working with GitHub

Best Practices and Coding Standards

1. Writing Clean and Readable Code
2. PEP 8 - Python Style Guide
3. Code Refactoring Techniques

Advanced Projects and Case Studies

1. Building a Data Dashboard with Dash
2. Developing a Chatbot with Python
3. Real-World Data Analysis Projects

Career Development and Job Preparation

1. Python Job Roles and Opportunities
2. Building a Professional Portfolio with Python Projects
3. Preparing for Python Interviews
4. Networking and Continuing Education Resources

Conclusion and Next Steps

1. Recap of Key Concepts Covered in the Course
2. Actionable Steps for Advancing Your Career in Python
3. Continuing Education Resources and Learning Paths
4. Q&A and Open Discussion

Python - Core

1. Introduction and history.
2. Setting up Python environment.
3. Basic syntax and data types.
4. Control flow and loops.
5. Functions and modules.

Python - Advanced

1. Object-oriented programming.
2. File handling and exception handling.
3. Introduction to data analysis libraries.

Project Work: Python - Data Analysis

1. Exploring Python libraries.
2. Data manipulation with NumPy and Pandas.
3. Data visualization with Matplotlib and Seaborn.
4. Working with databases and web scraping.