Get a first look at Julia, the powerful and fast programming language for data science and analytics.
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Get started in data mining. This introduction covers data mining techniques such as data reduction, clustering, association analysis, and more, with data mining tools like R and Python.
Data science never sleeps. Stay on top of the latest trends, tools, and techniques with weekly tips designed to make data scientists better at their jobs.
Get a comprehensive introduction to the careers, tools, and techniques of modern data science, including big data, programming, and statistics.
Learn how to use SPSS to calculate descriptive and inferential statistics, create data visualizations like scatterplots and other charts, perform multiple-regression analysis, and more.
What is big data? Explore its impact on consumers, businesses, and scientific research, and the methods behind storing, manipulating, and analyzing it.
Use R to model statistical relationships using its graphs, calculations, tests, and other analysis tools.
Challenge yourself with this series of real-world data visualization scenarios in Processing, an open-source drawing and development environment.
Introduces the R statistical processing language, including how to install R, read data from SPSS and spreadsheets, analyze data, and create charts and plots.
Discover how to create compelling data visualizations using Processing, an open-source drawing and development environment.
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