The Basics of Python is an introductory and beginners’ course to learning and understanding the fundamentals of coding in Python, a powerful, modern, industry demanding language. Participants will learn to write programs, perform various operations, manipulate and visualize data. Participants completing this course will be prepared to take up the advanced modules.
Python for Data Science is a beginners course in understanding how to code applications in Python, a powerful, modern and sought-after programming language.
Students will learn to write programs in Python which can perform calculations, retrieve and manipulate data, and visualize datasets with graphics (graphs and plots). Students who complete learning these skills will finish the course at a beginner level of Python and will be ready to take up intermediate and advanced courses in data analytics and science.
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The aim of the module is to get the participants familiar with the basics of the Python integrated development environment, the nuances of python scripting, basic operational functionalities and control structure used. Through this module students will be able to learn the basic nuances of Python, understand how to use the Python IDE and write simple codes, understand basic operations on Python, understand OOP functionality in Python, learn about control structure and looping in Python and will be able to write simple programs.
The objective of the module is to get the participants familiar with the OOP concepts within Python, working with files and strings and also with a popular tool – Jupyter. Through this the participants will learn how to work with external data sources, be it files or databases and also to write reusable codes on Jupyter and how it is useful as a presentation tool. This module will cover topics such as Classes, Methods, Attributes (PM), File I/O and Operations on Files (PM), Regular Expressions (PM) and Jupyter Notebooks (AM). This course aims to give students an insight in to learning to code using the OOP concepts in Python, learning how to access and get data from external sources, working with strings and text and writing code and presentation using Jupyter notebooks
This module will help the participants understand some of the most important libraries in python which are required for most operations: numpy (numerical python), pandas (data manipulation) and matplotlib (data visualization). These libraries will help the participants code more complex programs and visualize data using charts and graphs. It will also cover an important concept which involves use of scrapers to source data from the www and using APIs which are a critical part of any programming language. The topics covered within this module are basics of Numpy and Pandas (AM), Operations using Numpy and Pandas (PM), Data Visualization (Matplotlib) (PM) and Basics of Web Scraping and APIs (PM). Upon completion of this module students will be able to learn and code complex programs using Python Libraries, understand how to plot basic charts and graphs and will learn how to scrape data from the web and source data using APIs.
This course will take you through the fundamentals of Data Acquisition, Data Cleaning, Data Mining and various analytics & visualization techniques using libraries in Python.
Being able to predict the events in the future is a great asset to any business. This workshop focuses on how Python can be used for predictive analytics using various Python libraries.
It's time to upskill for the Industry 4.0