Course Timetable

Analysis and simulation, laboratory data acquisition and processing, measurement interfaces, engineering tools, computer systems organization, programming languages. Credit will only be given for one of: APSC_V 160, CPSC_V 301, or EOSC_V 211. [3-2-0].

Computation as a tool for systematic problem solving in non-computer-science disciplines. Introductory programming skills. Not for credit for students who have credit for, or exemption from, or are concurrently taking CPSC 110 or APSC 160. No programming experience expected. [3-0-1]

Design and analysis of basic algorithms and data structures; algorithm analysis methods, searching and sorting algorithms, basic data structures, graphs and concurrency. [3-2-0] Prerequisite: One of CPSC 210, CPEN 221 and either (a) one of CPSC 121, MATH 220 or (b) a score of 68% or higher in MATH 226.

Computer networking, basic communication protocols, network infrastructure and routing. Common application-level protocols and principles associated with developing distributed applications. [3-0-1] Prerequisite: CPSC_V 213 and either CPSC_V 221 or DSCI_V 221.

Application of machine learning tools, with an emphasis on solving practical problems. Data cleaning, feature extraction, supervised and unsupervised machine learning, reproducible workflows, and communicating results. [3-0-1] Prerequisite: Either (a) one of CPSC_V 203, CPSC_V 210, CPEN_V 221, DSCI_V 221 or (b) MATH_V 210 and one of CPSC_V 107, CPSC_V 110.