**Data Science Tutorial Course Free**

__About the Tutorial__

Data Science, one of the fastest-growing field has been in high demand as organizations are looking for making optimal use of their data. **Beginning with Data Science** is a comprehensive course where you would be learning the fundamentals of Data Science, like data measurement, charts and graphs, measures of central tendency and shapes.

As we move ahead we would also have a deep insight into Hypothesis Testing, Anova, basics of R Programming, Clustering, Regression Analysis, Correlation and Data mining. To simplify learning we have structured the course with appropriate examples and recommend you to practice the examples on your own. The Data Science course includes the theory and practicals of SAS, R Programming, Python.

__Why learn this course?__

Data Scientist is considered to be the sexiest job of 21^{st} century. According to a recent search, a Data Scientist, IT, earns Rs. 6 Lakhs per year. Companies like Google, Amazon, Facebook, Baidu have been making huge investments in data processing resulting in higher demands for the skillsets in Data Science.

If you want to make your career in Data Analytics or if you want to make the best out of your data leveraging your business to the next level, then you should take this course.

__Who can learn this course?__

You are a developer and seeking a move to Data Science, or a Business Analyst looking for a shift into Data Analytics, then you would find this course highly beneficial. The course would definitely be useful for professionals from Mathematics, Statistics, or Economics background and interested for learning Business Analytics.

Grab the ticket to get on boarded in top IT Giants like eBay, Amazon, Microsoft, PayPal, Apple etc, whose search for talented Data Science Experts is on constant rise.

__Pre-requisites__

Fundamentals of computers

Knowledge of basic statistics, excel and Mathematics would be highly beneficial

## Portal

Really helpful.

## Very Good

Nice to have such great clarification on data science.

I will recommend for all.