No prior experience is required. We will start from the very basics
What will I Learn and Apply post-program:
We build your foundation by going through the basics of Mathematics, Statistics and Machine Learning using our foundation training program on Data Science – DS1 Module:
In our DS1 Module You will Learn:
1)Descriptive & Inferential Statistics
4)Data Distributions – Discrete/Continuous
5)Matrix Algebra, Coordinate geometry & Calculus
6)CRISP-DM Framework 7)Machine Learning – Part 1
8)Python Programming – Adv
9)Simple & Multiple Linear regression with case studies
A Data Scientist dons many hats in his/her workplace. Not only are Data Scientists responsible for business analytics, but they are also involved in building data products and software platforms, along with developing visualizations and machine learning algorithms
Data Analytics career prospects depend not only on how good are you with programming —equally important is the ability to influence companies to take action. As you work for an organization, you will improve your communication skills.
A Data Analyst interprets data and turns it into information that can offer ways to improve a business, thus affecting business decisions. Data Analysts gather information from various sources and interpret patterns and trends – as such a Data Analyst job description should highlight the analytical nature of the role.
Key skills for a data analyst
R for Data Science:
This session is for “R for Data Science”. We will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it. In this session, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualizing and exploring data.
Why learn it?
Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines.
***What you get***