DASC 21103 — Principles and Techniques of Data Science
Principles and Techniques in Data Science is an intermediate semester-long data science course that follows an overview of data science in today's world. This class bridges between introduction to data science and upper division data science courses as well as methods courses in other concentrations. This class equips students with essential basic elements of data science, ranging from database systems, data acquisition, storage and query, data cleansing, data wrangling, basic data summarization and visualization, and data estimation and modeling. Students will gain hands-on experience using Python and various packages in Python. Pre- or Corequisite: DASC 25904 . Corequisite: Lab component. Prerequisite: ( DASC 100H3 or DASC 10003 ), ( DASC 11004 or ( DASC 16003 and DASC 10201 )), ( DASC 122H3 or DASC 12203 ), DASC 12004 , ( MATH 25004 or MATH 250H4 ), and the student must be a DTSCBS major. (Typically offered: Fall)
Prerequisites: DASC 10003, DASC 11004, DASC 16003, DASC 10201, DASC 12203, DASC 12004, MATH 25004