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Cool Class: Introduction to Data Science

April 11, 2019
Anjali Thapar

Taught by Professor of Psychology Anjali Thapar

What's Cool: I developed this course because of my own interests in the field of data science and because of my belief that the influence of data science can be seen everywhere in everyday life and that having skills and knowledge in data science will play a huge role in our students’ career development, regardless of their professional goals.  

Thanks to all of the hyper-connected objects (smart phones, vehicles, social media, etc.,) as a society we are collectively creating vast amounts of data on a daily basis. The goal of data science is to make sense of the data. In many ways, data scientists are statistical sleuths, data detectives who try to find and extract the hidden patterns and connections in the data to help answer questions related to all aspects of our lives.

The goal of the course is to provide students a broad introduction to the field of data science and to data analysis techniques using the statistical programming language R. The course is designed for students with little or no previous exposure to programming or statistics. Over the semester, students will work with publicly available datasets on topics related to real-world issues in health, population, energy, and politics and learn coding techniques in R for manipulating, processing, summarizing and visualizing large-scale datasets to extract meaning from data. I am excited to have to the opportunity to offer this course and to share my passion for research and data science.

Course Description: “Data Science” is a catch-all term used to describe the practice of working with and analyzing large-scale datasets to draw meaningful conclusions. This course provides a broad introduction to the field of data science via the statistical programming language, R. Over the semester, students will learn programming techniques in R for manipulating, processing, summarizing and visualizing large-scale datasets. No previous exposure to programming or statistics is expected.


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Department of Psychology

Department of Data Science

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