The Data Science Academy uses the ADAPT: All-campus Data science through Accessible Project-based Teaching and learning model for its courses. Learn more about the ADAPT model and what it means for your course.
The ADAPT: All-campus Data science through Accessible Project-based Teaching and learning model is a way of designing student-focused courses.
The data science courses offered by the Data Science Academy (DSA) share common elements, including:
- 1-credit special topics with the DSC 495 prefix.
- 1-credit courses = 50 minutes in class and no more than 3 hours of out-of-class work each week.
- Courses open to undergraduate students, graduate students, postdocs, staff and faculty as well as non-degree students.
- Students may take as many of the courses as they wish but may not repeat a course without instructor permission.
- Courses provide a bite of data science with a goal that students complete the course and choose to take more data science courses in the future.
- Project-based classes. No quizzes, no tests. Yes, homework. Yes, building to a final project.
- Final project built over the semester, not a crunch at the end while students need to focus on finals.
ADAPT data science courses fit into one of three levels: No Prerequisites, Suggested Skills and Research Ready.
- No Prerequisites (Level 1) means that courses do not require any previous data science knowledge or skills.
- Suggested Skills (Level 2) means that course descriptions include suggested skills and/or topical knowledge. Suggested skills can be acquired by coursework, self-directed study, work or other experiences.
- Research Ready (Level 3) means that students are invited to use their own research data to complete course activities. Courses may focus on ‘hot topics’ for academic, industry, non-profit or community-based research.
More About ADAPT
For more information about the ADAPT model used for Data Science Academy courses, you can review our Data Science Academy Courses: ADAPT Design, Descriptions and Schedule document.