This AoF allows students to manage data-sets (spreadsheets, relational databases, non-relational databases, and scripting across all); it is also ideal for non-CS majors (especially those from the social sciences, HSHP, Business) who generate progressively growing amounts of data. Here are the relevant courses as well as the prerequisite relations among them; those in blue are required, those in yellow are for electives for deeper experience.
- Principles of Structured Data: This course starts with an in-depth coverage of Google Sheets followed by a brief introduction to relational databases. Daily and weekly projects are based on real-world datasets.
- Introduction to Scripting: This course is designed for "Principles of Structured Data" students (past or concurrent) to get a preliminary experience with coding. Via scripting in Google Sheets, it covers fundamentals such as lists, list of lists, branching, loops, and functions. All exercises are designed to utilize students' existing knowledge of spreadsheets. As a final exercise, students add new and practical functionality to Google sheets.
- Discrete Structures: This course covers the mathematical topics needed by Computer Science students. Topics include logic, sets, functions, relations, combinatorics, and discrete probability. Lab work is conducted with Google Sheets.
- Principles of Computer Science I: [Python-based] This course is an introduction to solving problems by writing code. Students will become competent introductory python programmers, knowing how to design, develop, test, and analyze python code. They will be comfortable with the basic coding structures that are present across many programming languages, such as if statements, loops, and functions.
- Principles of Computer Science II: [Python-based] This course reinforces and strengthens the concepts learned in "Computer Science I". It introduces object-oriented programming, functional programming, and basic algorithmic analysis. End-of-semester projects make use of APIs and libraries to access real-world data-sets and explore how programs can be useful to other disciplines or areas of interest.
- Relational Database Systems: [SQL, JS, Python] This course is comprehensive coverage of the relational model via the Standard Query Language (SQL) including design and optimization. Student databases are hosted on the cloud. The visualization of the underlying data as well as map-oriented display of spatial information (i.e. Geographic Information Systems) are also studied.
- Topics Database Systems: This course is a continuation of "Relational Database Systems". It covers contemporary database topics such as noSQL databases, visualization, data-warehousing, and cloud-based infra-structures.
And here are the above courses in the context of our entire curriculum:
