Data Science
Employ a multiparadigm approach for your data science projects. Develop modular, flexible and scalable workflows to import, process, analyze and visualize data. Learn about easy-to-use functions, repositories, frameworks and interfaces while applying algorithms and techniques from across multiple disciplines.
These courses showcase some of the computational processes driving data analysis and visualization, the application of automated machine learning tools and the use of natural language queries within a symbolic framework. Topics covered also include the use of interactive Wolfram Notebooks and the cloud for generating reports and deploying data products. Earn course completion certificates and work toward Level 1 and Level 2 data science certifications.
Upcoming Events
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June 16 | Online
Wolfram Language for Python Users
See how Wolfram Language's unique computational framework can add functionality and accessibility to your existing Python workflows.
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June 23 | Online
Data Visualization with Wolfram Language
Using a curated dataset from the Wolfram Data Repository, this course demonstrates how to quickly visualize different data structures and prepare publication-ready graphics to share. Both domain-specific functions and general techniques are presented to help you get the most out of your visualizations. The course is designed for anyone who wants to learn more about data visualization in Wolfram Language.
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Jul 1 | Online
Enhancements to Time Series and Tabular Frameworks and New Model Fitting
In Version 15, we have an improved version of TimeSeries, based on the Tabular framework that we introduced in Version 14.2. In Version 15, we're also introducing a powerful new, unified approach to data fitting and inference. The new function ModelFit supports quantities and dates natively and works with both machine learning and statistical models.
