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Wolfram U offers free open interactive courses, learning events and other educational resources for professional and technical development.
Master linear algebra fundamentals through concise videos, interactive notebooks, and real-world applications. Covers linear equations, matrices, determinants, eigenvalues, and more, preparing you for advanced studies in data science and engineering.
Discover a visual approach to data science using Wolfram Language. Explore curated data, customize visualizations, and apply statistical concepts through hands-on examples and built-in functions.
Comprehensive Wolfram Language programming series covering fundamentals, practical applications, and advanced development techniques for certification preparation.
Learn Wolfram Language basics through video lessons covering notebooks, programming, visualization, data analysis, machine learning, and cloud deployment. Prepare for Level 1 certification and gain practical skills.
Comprehensive introduction to Mathematica, covering algebra to calculus with practical examples. Learn computational notebooks, plotting, graphics, equation solving, and more from an experienced instructor.
Explore data visualization techniques using Wolfram Language, covering various plot types, styling, labeling, arrangement, and interactive features for creating impactful graphics.
Quickly master Wolfram Language's symbolic programming, built-in functions, and data integration. Learn to read, understand, and write code in this powerful language tailored for programmers.
Enhance Wolfram Language skills with advanced patterns, coding practices, interactive interfaces, and cloud deployment. Ideal for programmers ready to create efficient, maintainable projects.
Learn to spot fraudulent behavior by analyzing data variations, comparing datasets, and conducting hypothesis tests using computational thinking and statistical methods.
Explore cause vs correlation through interactive activities, learning to analyze dependencies, interpret data, and critically evaluate media claims about causal relationships.
Explore gender effects on math scores using data analysis and visualization techniques. Learn to interpret results and present evidence-based opinions.
Explore randomness through interactive activities, learning to recognize and generate random outcomes using code. Investigate random noises, images, and shapes while understanding the importance of sample size and pseudorandomness.
Explore signal processing principles in LTI systems, covering continuous and discrete-time analysis, sampling, and filter design. Gain practical skills applicable to various scientific and engineering fields.
Explore global happiness data through interactive analysis, visualization, and interpretation, developing computational thinking skills to draw evidence-based conclusions.
Explore advanced Wolfram Language concepts: expression syntax, function definitions, upvalues, attributes, manual scoping, and package creation. Enhance coding efficiency and develop custom applications.
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