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Data science professionals rely on a range of tools, from basic spreadsheets to advanced languages like R and Python.

Data science is a process. This overview describes the 16 steps involved in the data science pathway.

Data science is sexy because it is one of the highest paying, most in-demand jobs around.

While data science relies heavily on statistical concepts, data science brings additional elements that make it a significantly ...

Statistics is distinct from – but critical to – data science. In this non-technical, conceptual overview, learn how statistical practices ...

Mathematics forms the foundation of data analysis. This presentation introduces some common mathematical concepts as used in ...

What exactly is data science, where did it come from, and why is it more important now than ever? annotated transcript: ...

For those learning to code, the concept of functions does not come naturally. Kaiser explains functions, what they do, their general ...

This video is part of the virtual useR! 2020 conference. Find supplementary material on our website https://user2020.r-project.org/.

In this video we learn about centrality algorithms, which are one of the traditional categories of graph algorithms. You can read ...

Data science sits at the intersection of coding, math/statistics, and applied domain knowledge. This video explores those ...

The statistical analysis of data is at the heart of data science. This overview introduces the most important concepts of analysis for ...

Part of the NERSC New User Training on June 16, 2020. Please see ...

This video is about missing data. Missing data is sneaky. In time series settings it is important to impute these values, but you can't ...

Big data and data science share many important elements, but this video shows how they represent conceptually distinct areas of ...

Ensure your works legacy. Future proof it with the principles of reproducible research.

This video is a part of Introduction to Data Science video series that dives into machine learning, visual analytics, and joys of ...

The purpose of data science is to direct behaviors. Make sure you analysis supports actionable insights.

Python for Data Analytics and Data Science 1. The whole python ka chilla for data science (Free main) is at this link: ...

Exploratory statistics allow you to get a well-informed and flexible understanding of your data. For more on this topic – and all of ...