DATA 3010: Introduction to Data Collection and Wrangling
This course provides an intensive introduction to data collection, wrangling, and summarization using the R programming language. Students will learn the fundamental skills required to collect, re-shape, transform, manipulate, analytically explore, summarize, and visualize data. Students will learn how data must be organized and formatted in order to perform effective data analysis or be inputted into a machine learning algorithm. Further, students will learn how to produce data-driven dynamic web applications. The time students allocate to learn these data-related skills will allow them to create data sets that promote more efficient, reproducible, and understandable data science products. The course is designed for students from any major with real-world examples drawn from a variety of domains. Students of all skill levels are welcome, including those with limited or no statistical, mathematical, or programming backgrounds. All necessary skills will be taught in class.
Course Goals
- Apply knowledge and techniques from the course to collect a variety of data types.
- Create "refined" data sets that are amenable to statistical analysis or for use with machine learning algorithms.
- Evaluate different data types and determine what data processing techniques are required to make those data types useable.
- Implement a variety of data processing techniques.
- Understand the differences in data structures and how this may affect data processing.
- Create summaries of constructed data structures in tabular, graphical, and textual form.
- Create dynamic data-driven web applications that combine information about data in innovative tabular, graphical, and textual representations.
- Become more comfortable and proficient in using statistical programming language to solve data-related problems and questions.
This 3-credit hour course has no prerequisites and is open to all students. Sections are taught by CAIDS Professor of Practice, Lisa Dilks.
Prerequisites
This course has no prerequisites.
Ready to take this course?
Search for "DATA 3010" in the Schedule of Classes to register. For more help with registration, please review the resources provided by the Registrar's Office.
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