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.

Specification, design, validation, evolution and construction of modern software systems, within the context of socially and professionally relevant domains such as ethics, intellectual property, and information security. [3-2-0] Prerequisite: All of CPSC 213, CPSC 221.

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.