Technical Foundation for Data Science Success

Focused on practical applications, this course covers the foundational concepts from programming, linear algebra, calculus, probability, and statistics that are most relevant to technical data science skills in the curriculum. At the end of the course, all students will achieve a baseline level of technical knowledge to prepare them for the technical components of the program. Learners will have the opportunity to explore more in-depth topics to discover how foundational topics like derivatives, matrices, and distributions are applied in machine learning and data modeling. Examples are drawn from advanced courses to highlight how these tools can be applied to theories and practice examined in this course.