An introductory course
where students will learn how to gather, analyze and visual large collections of data to extract knowledge for decision-making.
Students will learn how to...
- Articulate the decision process, including decision biases and qualitative and quantitative variables.
- Frame a data problem from the story of a subject matter expert.
- Identify exceptional cases using measures of central tendency.
- Ask questions to quantify risk and uncertainty.
- Identify and analyze security concerns and ethical issues in a data problem.
- Merge different sources of data in complimentary ways.
- Use an appropriate programming language to help process and format data.
- Use boolean logic and conditional expressions to automate decision making.
- Write functions to automate processes and reuse code.
- Use looping techniques to solve problems that require iteration.
- Use appropriate software packages and libraries to create data visualizations.