Course Info: CS-0243
| Course | CS-0243 Introduction to Data Science |
| Long Title | Introduction to Data Science |
| Term | 2018S |
| Note(s) |
Satisfies Distribution Textbook information |
| Meeting Info | Adele Simmons Hall 126 on T,TH from 12:30-1:50 |
| Faculty | Ethan Meyers |
| Capacity | 20 |
| Available | 5 |
| Waitlist | 0 |
| Distribution(s) |
Mind, Brain, and Information |
| Cumulative Skill(s) | Quantitative Skills |
| Additional Info | In this course, students are expected to spend at least six to eight hours a week of preparation and work outside of class time. This time includes reading, writing, research. There is a $10 lab fee for this course |
| Description | Data Science is a field that uses computational tools to extract insight from large data sets. This class covered several key topics in Data Science including data visualization, data cleaning/wrangling, making predictions from data (machine learning), and manipulating text. Students learned how to use the R programming language to analyze data by engaging with seven homework assignments (five worksheets and two DataCamp exercises), along with larger midterm and final class projects. Students also gave three class presentations to practice communicating quantitative information, and they commented on nine data journalism articles to learn more about ongoing work in the field. By successfully completing this class, students will have the ability to extract and communicate useful insights from real data sets. |