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An Elementary Introduction to the Wolfram Language
Interactive Course | FREE

Requirements: This course requires no prior knowledge of Mathematica or the Wolfram Language.

Certification Levels: CompletionLevel 1

Learn the Wolfram Language and modern computational thinking from Stephen Wolfram's book with veteran Wolfram Language instructor and developer David Withoff. The course requires no prior programming knowledge and is suitable for those at any educational level with an interest in computational thinking and its practical applications.

Course Overview
  • Section 166 minutes
  • Section 269 minutes
  • Section 355 minutes
  • Section 479 minutes
  • Section 5100 minutes
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Computational Xplorations
Instructor Led | FREE

Requirements: This course requires no prior knowledge of Wolfram Language or Mathematica.

Certification Levels: Completion

Join this free introductory course to discover how to interactively explore nearly any field using computation. See how computational thinking—a modern blend of critical analysis and information processing—is being applied to a range of disciplines not traditionally associated with coding. From nutrition to literature, you'll learn practical ways to use knowledge-based programming in your classroom, research project or company. This class introduces innovative methods for discovering ideas and insights using the computational intelligence of the Wolfram Language, the user-friendly coding environment of Wolfram Notebooks and the curated real-world knowledge of the Wolfram Knowledgebase.

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Daily Study Group: EdTech for the Computational Classroom
Special Event | FREE

Certification Levels: Completion

Join this Daily Study Group and discover how painless it can be to bring computational learning to all course subjects. Start with a broad overview to get a sense of what's possible with Wolfram technology, from interactive graphs and geographic plots to financial and historical data analysis. Instructors will see student examples of computational lab notebooks exploring subjects like math, physics and computer science and learn how to create quizzes and exams with Wolfram's new question and assessment framework.

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Can I Spot a Cheat?

Can I Spot a Cheat?
Interactive Course | FREE

Requirements: This course requires basic working knowledge of the Wolfram Language, common data visualisations (histograms) and empirical and probability distributions.

Certification Levels: CompletionLevel 1

Being able to measure variations in data and identify abnormal variation is an important skill in many fields. In the financial sector, for example, fraudulent behaviour can cost huge sums of money. In this Computational Thinking module, you will learn how to recognise patterns in data that differ “significantly” from the norm and learn how to provide evidence that the source of one dataset is different to another. You will learn how to use significance levels to quantify how unexpected the patterns or differences were, ultimately writing and interpreting your own hypothesis test.

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Cause or Correlation?

Cause or Correlation?
Interactive Course | FREE

Requirements: This course requires basic working knowledge of the Wolfram Language, common data visualisations (histograms) and statistics (mean, median).

Certification Levels: CompletionLevel 1

Knowing how one variable affects another is important in many instances in real life, from medical diagnoses to environmental impacts or financial trends. In this Computational Thinking module, you will learn about dependent connections between variables, the possible cause(s) for such dependencies and how these are often misused in the media to make claims that are incorrect—particularly about how adopting one behaviour can cause something positive or negative to happen.

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Does Gender Help with Your Maths Score?

Does Gender Help with Your Maths Score?
Interactive Course | FREE

Requirements: This course requires knowledge of common data visualisations (pie charts, bar charts, histograms) and statistics (min-max, mean, median, range).

Certification Levels: CompletionLevel 1

The ability to decide whether group A is different, either better or worse, than group B is an important technique within computational thinking and data science. It is useful in many areas, from medical experiments to sales figures to environmental changes. This Computational Thinking module introduces you to how problems like this can be tackled, first on small datasets, then on a national scale, comparing results to published reports.

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How Happy Are People in My Country?

How Happy Are People in My Country?
Interactive Course | FREE

Requirements: This course requires knowledge of common data visualisations (bar chart) and statistics (mean, median), as well as very basic spreadsheet skills.

Certification Levels: CompletionLevel 1

Happiness, like many other subjective measures, is difficult to define. But with careful assumptions, many governments and businesses can analyse subjective data and use it to improve future growth or the lives of their citizens. In this Computational Thinking module, you will learn how the assumptions are made and how data scientists analyse reliable sources of data, ultimately finding a measure of how happy people are in your country.

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That's Random! Or Is It?

That's Random! Or Is It?
Interactive Course | FREE

Requirements: No particular prior knowledge of randomness is required. Knowing how to interpret a bar chart and understanding the terms integer, 2D and 3D would be beneficial.

Certification Levels: Completion

From selecting lottery numbers to testing new medicines, making sure something is truly random is important business. In this Computational Thinking module, you will learn how to recognise randomness, understand what makes something truly random and see how sample size can affect your opinion of randomness. You will explore what random noises, images and shapes look like before going on to generate your own. By learning how to use code to generate these random outputs, you will learn about pseudorandomness—computers’ attempt at true randomness.

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