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The GreyCampus Blog

A dedicated blog for professional certifications across world. GreyCampus provides abundant resources on professional certification like PMP, Six Sigma, ITIL and more.

Top 10 Libraries of Python for Data Science

In this article, we shall explore the various python libraries that data scientists possess in their toolkit. From libraries for number crunching to ML algorithms and visualization, this list includes all the prominent python libraries for data science as of 2020.

How to Become a Data Scientist in 2020

What does it take to become a Data Scientist? How do you go about gaining the skills to become one? This 1-hour webinar will bring you up to pace on the pre-requisites and skill path to get your foot in the Data Science door.

How can Machine Learning benefit Cloud Computing?

Over the past 3 years, many cloud service providers have made significant investments in Artificial Intelligence and Machine Learning. In this article, read about the benefits these technologies have to offer in cloud computing.

Machine Learning for Dummies - A quick guide

Want to choose Machine Learning as a career option? Then here’s the article that helps you understand everything you need to know about Machine Learning before you decide on it. In this article, the author also explains to you how Machine Learning and Artificial Intelligence are related.

How to drive Business value with Robotic Process Automation(RPA)?

In the current era of digitalization, RPA has become a key enabler to support digital transformation across a wide range of industries. This article illustrates how RPA has a strategic impact on meaningful business processes and will continue to be an exceptional driver of value for businesses globally.

Business Analytics and Data Science: Webinar

In this webinar, we take you through the concepts of Data Science and elaborate on how disruptive the data has been over a period of time and the reason why we are entering into the concept of Big Data. In this piece, we shall learn about predictive and prescriptive analytics, statistical inferences, like Statistical Learning versus Machine Learning, how different are they and at what level they separate themselves from each other.