| Term | Evaluations | Course rating | Instructor rating |
|---|---|---|---|
| Spring 2025 | 2 | 4.1 | 4.1 |
| Fall 2024 | 2 | 4.6 | 4.8 |
| Summer 2024 | 1 | 4.3 | 4.6 |
| Spring 2024 | 2 | 4.6 | 4.5 |
| Fall 2023 | 2 | 4.0 | 4.1 |
The course provides students with an overview of popular software packages used today for data exploration, analysis and visualization. The first part of the course will offer an overview of the non-programming tools Excel and Tableau. In Excel we will cover basic charts with the emphasis on their use with pivot tables. In Tableau students will be introduced to more advanced data exploration and visualization methods via a variety of advanced charts and dashboards. The second part of the course will cover exploratory data analysis in R. Here students will learn how to write their own code for importing, cleaning and exploring large datasets, as well as how to create, modify and export complex charts and summaries for visual, qualitative and quantitative analysis of the data. The third part of the course will provide an intro to using SQL databases, where students will learn how to create SQL queries to select, filter and manipulate the data.
Estimated from the original workload response buckets. Individual sections may differ.
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