59% of companies plan to increase positions requiring data analysis skills

Thanks to the digital revolution that is sweeping the world and India in particular, data ​scientists are now the most sought-after professionals by big corporations as well as startups. Companies across industries are rewarding good ​data ​analysts​ and scientists​ with desirable career growth and salaries.

Being able to tell a story using data is more critical than ever. Rapidly expanding companies understand this and are therefore seeking data professionals who go beyond crunching numbers and can craft narratives that support decision making.

If you torture data long enough, it will confess.

Ronald CoaseClifton R. Musser Professor of Economics at the University of Chicago Law School
These numbers craft a tell-all

5,00,000 Projected Job Openings For Data Scientists In 2018 by NASSCOM

92% of Fortune 500 organizations will need to exploit big data by 2020 to stay in the game. Analytics Firms In India are Facing a Shortfall of over 2,00,000 skilled Data Analysts. Projected growth in global data generated each year is 40%.

Connect these three dots. You will then understand the relevance of Data Analytics Expertise in the industry today.

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Data Analytics certified individuals break into the $100,000+ pay and are among the highest-paid professionals globally

Data Visualisation

The latest generation of visualisation tools is easy to adopt and offer an immediate business advantage and effective storytelling. They can also be a useful way of establishing best practice ways of looking at your data.

Self-service analytics

There is a misconception that working with data requires advanced programming skills. This might have been the case in the past, but with the rapid developments in technology the barriers have been lowered.

Agile analytics

By combining raw data, a set of hypotheses and people with domain knowledge, analytics experts can quickly test iterative processes to create a working solution. Such quick delivery enables you to decide whether a long-term implementation is right for your business.

Data diversity

More data often means more insight. But it isn't always simple to obtain; data diversity requires tackling disparate sources, varied data sets and unstructured data. Employing the current wave of data blending tools, you can bridge the gap between all these sources.

Course Contents

R & Python Basics for Analytics

R & Python are the most robust environments for Data Analytics in the industry today.

Data Visualization

The goal is to communicate information clearly and efficiently to users. This is perhaps the most common application of Data Analytics.

Exploratory Data Analysis

These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models.

Data Manipulation

Changing the data in an effort to make it easier to read and more organized for effectively communicating with the end user.

Additional Topics

We cover the other topics which are add-ons to the above-mentioned topics for a holistic analytics learning.

Capstone Project

A detailed industry project at the end of the training that would provide deep insights into the industrial application.

Advance your data-crunching skills and refine your ability to work with messy, complex datasets.

Learn to manipulate and prepare data for analysis, and create visualizations for data exploration. Finally, you’ll learn to use your data skills to tell a story with data.

Useful packages in R & Python

Getting acquainted with the packages that used extensively by companies which are heavily invested in Data Analytics.

Supervised and Unsupervised Algorithms

Understanding the difference in these two and how the industry looks at them.

Industry Case-study solving

The entire classroom training will be conducted via case-study problem solving using industry datasets.

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