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Updated by Great Learning on Jan 02, 2020
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Data Science by Great Learning

Data Science is a field of science which deals with scientific methods, processes, modelling and algorithms to analyze and extract knowledge for the data, where the date can be both structured and unstructured. This science helps companies interpret and manage data to solve complex problems and gives insights to develop various business strategies.

Source: https://www.greatlearning.in/blog/category/data-science/

Characteristics of a Good Product Manager - Great Learning

A product manager is a part of every stage of the product be it design, build, test or market. Even if the product is an outsourced product, a product manager has a huge role to play. There are many qualities of a good product manager but what makes a manager great. Read on to know more.

Application of Data Science in E Commerce

E-commerce has been heavily dependent on data to improve its efficiency, so the applications of data science in e-commerce are massive. With so many players in the market, noone wants to be left behind in the race. Here's how the industry is leveraging data science.

Data Science in Fashion by Great Learning

The applications of Data Science have been far-reaching, and the fashion industry has been a surprising early-adopter. So much data on how the Fashion Industry is changing in today's world, it sometimes becomes difficult to make the right decisions. This is how the impact of data science in the fashion industry has been playing out.

Different Roles in Data Science - Great Learning

The Data Science sector has been booming for a while now, and there are a wide variety of jobs that are available. But seldom is anyone aware of the opportunities available in different industries. We explore the different kinds of job roles in the market currently, and what the job description entails.

Data Science Vs Artificial Intelligence - Great Learning

Data Science and Machine Learning might have overlaps, but they're still different. The main difference between the two is that data science as a broader spectrum which focuses on statistics, algorithms and entire data processing methodology. We explain what makes them different, and how that impacts their application.