Data Analysis and Representation, Selection and Iteration

This course is the second in a specialization that explores computational thinking and beginning C programming. Computational thinking is a problem-solving process that involves various components. The prerequisite knowledge for this course includes algorithms, procedures, data collection, data types, variable constants, and STEM computations. The course covers topics such as data analysis, data representation, and other computational thinking techniques. It also builds on programming knowledge by teaching how to implement selection and looping.

The course is divided into four modules. In Module 1, students learn about common statistics that can be calculated as they analyze data sets. Module 2 focuses on decision-making in code. Module 3 explores different ways to represent data sets. Finally, Module 4 teaches students how to use iteration or looping to repeat actions within their code.

Overall, this course provides a comprehensive understanding of data analysis and computational thinking techniques. Students need to have the prerequisite knowledge from either the previous course or personal experience before starting this course.