Course 1: Foundations
By the end of this course, students will have completed several small projects (sibling interviews, penguin species classification, and their own independent hypothesis testing). These lessons introduce students to the world of data and prepare them for academic research they will encounter in the second course.
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Core concepts: dataset exploration, metadata
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Concepts: sorting, filtering, COUNTIF()
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Core concepts: data aggregation, summarizing data
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Core concepts: frequency, data distribution, bins
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Lesson 4: Building a Penguin Classifier
Core concepts: classification (intro), IF() statements, logic
Core concepts: classification (intro), IF() statements, logic
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Core concepts: problem formulation, research question
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Concepts: variable identification, cause and effect
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Core concepts: null hypothesis (H0), alternative hypothesis (Ha)
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Core concepts: correlation, causation, confounding variables
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Lesson 4: Science Communication
Core concepts: drawing conclusions, data storytelling with short form video
Core concepts: drawing conclusions, data storytelling with short form video
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Learn the way you are supposed to learn.
Course 1 introduces you to the magic of data science in an engaging project-based format. Learn to collect and compare data, explore existing datasets to find new trends, and even test your own hypothesis. In the end, you will learn to communicate your findings to a broad audience in an academic format. Who said learning can’t be fun?
