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 160, CPSC 301, or EOSC 211. This course is not eligible for Credit/D/Fail grading. [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]

Fundamental computation and program structures. Continuing systematic program design from CPSC 103. [3-2-0] Prerequisite: CPSC 103.

Physical and mathematical structures of computation. Boolean algebra and combinations logic circuits; proof techniques; functions and sequential circuits; sets and relations; finite state machines; sequential instruction execution. [3-2-1] Prerequisite: Principles of Mathematics 12 or Pre-calculus 12. Corequisite: One of CPSC 107, CPSC 110.

Design, development, and analysis of robust software components. Topics such as software design, computational models, data structures, debugging, and testing. [3-2-0] Prerequisite: One of CPSC 107, CPSC 110.

Software architecture, operating systems, and I/O architectures. Relationships between application software, operating systems, and computing hardware; critical sections, deadlock avoidance, and performance; principles and operation of disks and networks. [3-3-0] Prerequisite: All of CPSC 121, CPSC 210.

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.

Overview of database systems, ER models, logical database design and normalization, formal relational query languages, SQL and other commercial languages, data warehouses, special topics. [3-0-1] Prerequisite: CPSC_V 221 or DSCI_V 221.

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.

Systematic study of basic concepts and techniques in the design and analysis of algorithms, illustrated from various problem areas. Topics include: models of computation; choice of data structures; graph-theoretic, algebraic, and text processing algorithms. [3-0-1] Prerequisite: All of (a) CPSC_V 221 or DSCI_V 221, (b) at least 3 credits from COMM_V 291, BIOL_V 300, MATH or STAT at 200 level or above.

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.

Concepts and design of distributed systems. Communication architecture and models for interprocess communication. Process migration, naming, distributed file systems, fault tolerance, and concurrency control. [3-0-0] Prerequisite: One of CPSC 313, CPEN 331 and one of CPSC 317, ELEC 331.

Hands-on project, mentored by industry experts, integrating skills relevant to early career in the computing industry: technical skills, communication, teamwork, networking and portfolio building. [2.5-2-0] Prerequisite: One of CPSC 310, CPEN 321.