Data is the new Oil. This statement shows how every modern IT system is driven by capturing, storing and analysing data for various needs. Be it about making decision for business, forecasting weather, studying protein structures in biology or designing a marketing campaign. All of these scenarios involve a multidisciplinary approach of using mathematical models, statistics, graphs, databases and of course the business or scientific logic behind the data analysis. So we need a programming language which can cater to all these diverse needs of data science. Python shines bright as one such language as it has numerous libraries and built in features which makes it easy to tackle the needs of Data science.
In this tutorial we will cover these the various techniques used in data science using the Python programming language.
Course Fee: ₹15,000 ₹3,000 (discount closing soon)
This course is designed for graduates as well as Professionals who are willing to learn data science in simple and easy steps using Python as a programming language.
Before proceeding with this course, you should have a basic knowledge of writing code in Python programming language, using any python IDE and execution of Python programs. If you are completely new to python then please refer our Python course to get a sound understanding of the language.
Skill level: Beginner Level
Languages: English
Certificates: Get SBMEC certificate by completing entire course.
Data Science is an evolving field and Python has become a required skill for 46-percent of jobs in Data Science. The demand for Data Science professionals will grow an estimated 1581-percent by 2020 and professionals with Python skills will have an additional advantage.
Get complimentary guidance to placement to ace your internship/job hunt.
Chance to work on live projects and get better understanding of topics.
Your training is packed with assignments, assessment tests, challenges, quizzes and exercises.
At the end of your training program you will be awarded with certificate of completion*.