Python Training

Python is a versatile and powerful programming language known for its simplicity and readability. It is widely used for web development, data science, artificial intelligence, automation, and more. With its vast libraries and frameworks, Python enables developers to build robust and scalable applications efficiently.Python is renowned for its simplicity and readability, making it a great language for beginners. At the same time, its vast range of libraries and frameworks makes it incredibly powerful for professionals working in data science, web development, and automation.

Introduction to Python

What is Python and why use it?
Installing and setting up the Python environment.
Basic Python syntax and structure.
Variables, data types, and operators.

Python Programming Fundamentals

Control structures: if/else, loops (for, while).
Functions: defining, calling, and passing parameters.
Lists, Tuples, and Dictionaries: Working with Python collections.
String manipulation and regular expressions.

Advanced Python Features

File handling: reading, writing, and manipulating files.
Exception handling: try-except blocks for error management.
Modules and Packages: Creating and using Python modules.
Working with JSON and XML data.

Database Integration with Python

Connecting to databases using SQLite, MySQL, or PostgreSQL.
Performing CRUD (Create, Read, Update, Delete) operations.
Using ORM tools like SQLAlchemy for database interactions.
Understanding database transactions and queries.

Python Frameworks (Optional/Advanced)

Introduction to web frameworks like Flask and Django.
Building RESTful APIs with Flask or Django REST Framework.
Creating web applications using MVC architecture.

Deployment and APIs

Deploying Python applications on cloud platforms.
Using APIs for data exchange and integration.
Working with third-party APIs.

Object-Oriented Programming (OOP) in Python

Introduction to classes and objects.
Encapsulation, inheritance, and polymorphism.
Abstract classes and interfaces.

Working with Data Science and Automation

Introduction to libraries like NumPy, Pandas, and Matplotlib.
Data analysis and visualization techniques.
Automating tasks with Python scripts.