In this one-day workshop, graduate students will learn about the pedagogy of the Data Science Education Program. This workshop will cover some of the computational and statistical concepts that students learn in the Foundations of Data Science class (Data 8) and Principles and Techniques of Data Science (Data 100), as well as an overview of the Connector courses and Modules. It will also give experience using a cloud based computing environment. Graduate students can use these skills to improve teaching, to imagine new types of teaching, and learn what resources are available. Open to UC Berkeley graduate students. No previous programming or statistics experience needed.
June 7, 2019 at the Academic Innovation Studio, 117 Dwinelle Hall
Registration
Contact: Eric Van Dusen ericvd@berkeley.edu
Workshop Topics
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Overview of Data 8: inference, computational thinking, and Python
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Introduction to Data 100: Principles and Techniques of Data Science.
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Data-Centered Computing Environment: tables in the cloud, computational documents
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Learn to create and teach assignments within the Jupyter notebook system
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Sample lectures & labs from applied courses (Humanities, Social Sciences, Natural Sciences, Engineering)
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Understand the infrastructure behind the pedagogy platform
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Incorporate scientific reproducibility practices into teaching
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Learn about the work and student teams in the Data Science Education program