The Department of Mathematics, Statistics, and Computer Science regularly offers the Data and Computation Fundamentals (DCF) course:
This is your chance to get in on the ground floor — a small class team-taught by two professors. By doing so, not only will you be learning about Big Data and gaining useful skills, you’ll be helping to shape the curriculum for students in future years. Join us! There are no pre-requisites!
As a one-credit course, most students will be able to add the course to their existing schedule without any re-adjustment. The one-credit course will meet for 10 hours spread over eight weeks. It will also involve about a quarter of the work of a regular course.
The list of topics inlcudes:
- Introduction, data files, documentation markup, and elementary data visualization
- Relational database operations, intermediate data visualization
- More data operations, map visualization
- Basic models, fitting, and summaries
- Dimension reduction
- Putting it all together
You can examine the syllabus for this course at this link. Eventually the DCF course will be a co-requisite for courses such as Applied Calculus, Statistical Modeling, General Chemistry, and Genetics; over the next several years it will be ramped up to an expected enrollment of about 200 students per year.
Data and Computation Fundamentals (DCF)- linked courses
Co-enrollment or prior completion of the DCF course will be required for enrollment in the set of “DCF-linked” courses. Although science students will be required to take the DCF course only once, they will enroll in more than one of the DCF-linked courses and will apply data fundamentals in several different settings.
Instructors of these courses have all expressed willingness to participate in the Computation and Visualization workshops and intend to adapt, generate, and/or refine curricular materials for the introductory courses. The DCF course will be completed during the first third of the semester. Data computation and visualization modules in the DCF-linked courses will be deployed in the last two-thirds of the semester.
This organization allows students to refine fundamental data principles and skills in disciplinary contexts. Many students in these introductory science classes are enrolled to complete a natural sciences and mathematics general education distribution requirement. As such, these efforts also promote scientific and quantitative literacy among a broad range of students.