Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. It’s easy to learn simple syntax is very accessible to new programmers and is similar to Matlab, C/C++, Java, or Visual Basic. Python is general purpose and comparatively easy to learn with an increased adoption for analytical and quantitative computing. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.
Who should go for this course?
Experienced Professional or a Beginner, Anyone who wants to learn to programming with Python can start right away!
This course is exclusively designed for professionals aspiring to make a career in Big Data Analytics using Python. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of this widely-used open source general-purpose scripting language, can also opt for this course.
Although there are no hard prerequisites, attendees having prior programming experience and familiarity with basic concepts such as variables/scopes, flow-control, and functions would be beneficial. Prior exposure to object-oriented programming concepts is not required, but definitely beneficial.
Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python is continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, and Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next “Big Thing” and a must for Professionals in the Data Analytics domain.
Online Classes: 30 hours
Lab hours: 40 Hours
Project: 20 hours
Part time/ Full Time: Part time