Python Corporate Training Course

In this module, professionals get an overview of Python, its features, and its advantages over other programming languages. Then, they learn to install Python on operating systems such as Windows, Mac, and Linux. The module also covers variables, operands, expressions, data types, and conditional statements with practical demonstrations.

This module thoroughly explains the fundamental building blocks of Python programming, such as classes, modules, and objects. It also covers strings, sets, lists, tuples, dictionaries, and file handling. Besides, data structures- linked lists, stacks, queues, and control statements such as while, for, if, break, and else, are among the important topics covered.

The focus of this module is on object-oriented programming (OOP) concepts and their implementation in Python. The major topics covered are function parameters, different types of arguments, the OOPs paradigm, and important OOP concepts such as inheritance, polymorphism, constructors, destructors, encapsulation, and overloading. The module also covers exception-handling scenarios with execution examples, including arithmetic exceptions and value errors.

This module introduces participants to data analysis with NumPy and Pandas libraries. Participants will learn how to create NumPy arrays, perform operations on them, and use Pandas to create series and data frames. The module also covers topics- importing and exporting data, file operations with NumPy, manipulating and cleaning data with Pandas, and performing data frame operations.

Through this module, professionals gain expertise in plotting graphs and charts with Python, various aspects of line, scatter, bar, histogram, 3D, the API of MatPlotlib, subplots, saving plots, Grids, and Heatmaps. Also, learn to customize subplots and visualizations using Matplotlib.

In this module, professionals gain an understanding of Machine Learning concepts, Machine Learning types, and Linear Regression Implementation. In supervised learning, professionals will be focused on, Supervised Learning concepts, Implementing different types of Supervised Learning Algorithms, and Evaluating model output. In Unsupervised Learning, professionals will focus on various types of Unsupervised Learning Implementation of Clustering. Finally, in Reinforcement learning, professionals will be expertized in Implement Reinforcement Learning using Python, Developing a Q Learning model in Python.

The module on Database connection with MySql explains the basics of database management, Python MySql, how to create a database, Database Integration with Python, and work on database applications.

This module covers web frameworks such as Flask, Django, or Pyramid, which provide tools and libraries to make web development faster and more efficient in organizations. Also, concepts such as Introduction to Web Scraping in Python, Installing of beautifulsoup, Installing Python Parser lxml, various web scraping libraries, beautifulsoup, and Scrapy Python are packaged as part of the module.