Essential Math for Applied Data Science

This course is intended as a math "boot camp" for incoming DACSS students and PhD students in certain social and behavioral sciences. Students will develop or refresh math skills needed for effectively learning applied statistics and computational methods. Topics covered include essential algebra review (basic skills, functions, exponents and logarithms, trigonometric functions); key concepts from calculus and their applied use; probabilistic reasoning, calculation, and distribution functions; and fundamentals of matrix arithmetic and linear algebra. Students who have taken college courses in calculus, probability, and linear algebra should not take this class, which is a crash course/review of fundamentals.