Ani Adhikari

Adhikari writes on a variety of topics, from stochastic processes to women in mathematics, and regularly teaches both Statistics 2, “Introduction to Statistics” and Statistics 21, “Introduction to Probability and Statistics.” She has been instrumental in developing Statistics 300, “Professional Preparation: Teaching of Probability and Statistics,” not only expanding the syllabus to provide valuable training for GSIs, but serving as a mentor and role model for them.

More info: http://teaching.berkeley.edu/dta-recipient/ani-adhikari

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Data Science: Inferential Thinking through Simulations (edX)

Learn how to test hypotheses, draw inferences, and make robust conclusions based on data. Using real-world examples from a wide range of domains including law, medicine, and football, you’ll learn how data scientists make conclusions about unknowns based on the data available. In this course, you will learn the [...]
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Data Science: Machine Learning and Predictions (edX)

Learn how to use machine learning, with a focus on regression and classification, to automatically identify patterns in your data and make better predictions. One of the principal responsibilities of a data scientist is to make reliable predictions based on data. When the amount of data available is enormous, [...]
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Data Science: Computational Thinking with Python (edX)

Learn the basics of computational thinking, an essential skill in today’s data-driven world, using the popular programming language, Python. We live in an era of unprecedented access to data. Understanding how to organize and leverage the vast amounts of information at our disposal are critical skills that allow us [...]
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