QSC Employment

Teaching Positions Available for the School of Computing – Spring/Fall/Winter 2023-24

Posted on 2023/04/17 by Doug Martin

The School of Computing at Queen’s University invites applications from suitably qualified candidates interested in teaching courses shown below.

The University invites applications from all qualified individuals. Queen’s University is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, aboriginal people, persons with disabilities, and persons of any sexual orientation or gender identity. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Applications for Spring term will be received until May 1, 2023. Applications for Fall/Winter term will be received until June 15, 2023. Review of applications will commence shortly thereafter, and the final appointment is subject to budgetary approval. Additional information about the School of Computing can be found on our homepage.

Courses available are listed below.

Applying as a Term Adjunct.
Applying as a Teaching Fellow.

Academic Year 2023/2024 Spring Term

This spring term period is from May 1, 2023 to June 30, 2023.

Applications for Spring term will be received until May 1, 2023.

BMIF 801 – Programming Skills and Tools for Processing Biomedical Data (3.00 units)
The objective of this course is to provide graduating health science students hands-on training in computer programming languages and tools to familiarize them with the principles and practice of cutting edge technologies for bioinformatics used in biomedical and molecular sciences research.
Prerequisite: none

Academic Year 2023/2024 Fall Term

This fall term period is from September 1, 2023 to December 31, 2023.

Applications for Fall/Winter term will be received until June 15, 2023.

CISC 235 – Data Structures (3.00 units)
Design and implementation of advanced data structures and related algorithms, including correctness and complexity analysis.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 124 and CISC 203).

CISC 320 – Fundamentals of Software Development (3.00 units)
Introduction to management of small and medium-scale software projects. Advanced programming methodology using the programming language C++. Includes a significant programming project.
Learning Hours: 120 (36 Lecture, 24 Tutorial, 24 Group Learning, 36 Private Study)
Prerequisites: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 235.

CISC 324 – Operating Systems (3.00 units)
Layered operating systems for conventional shared memory computers: concurrent processes. Synchronization and communication. Concurrent algorithms. Scheduling. Deadlock. Memory management. Protection. File systems. Device management. Typical layers.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 221 and CISC 235).

CISC 327 – Software Quality Assurance (3.00 units)
Validation of software throughout the life cycle. Comparative effectiveness in defect removal of formal methods (proofs of correctness), inspection (walkthroughs and reviews), and testing (unit, integration, and system testing; white box versus black box).
Learning Hours: 120 (36 Lecture, 84 Group Learning)
Prerequisites: C- (or P in Winter 2020) in (CISC 220 and CISC 124) and registration in a School of Computing Plan.
Exclusion: SOFT 327

CISC 452 – Neural and Genetic Computing (3.00 units)
Introduction to neural and genetic computing. Topics include associative memory systems, neural optimization strategies, supervised and unsupervised classification networks, genetic algorithms, genetic and evolutionary programming. Applications are examined, and the relation to biologic systems is discussed.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 235.
Exclusion: COGS 400.

CISC 471 – Computational Biology (3.00 units)
Advanced computational approaches to the problems in molecular biology. Techniques and algorithms for sequence analysis and alignment; molecular databases; protein structure prediction and molecular data mining.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 352 and CISC 365).

CISC 486 – Game Development (3.00 units)
An introduction to ‘engines’ used in networked 3-dimensional games. Topics include game-engine architecture and components providing 3-dimensional rendering, physics simulation, sound, artificial intelligence and networking services.
Learning Hours: 120 (36 Lecture, 15 Group Learning, 69 Private Study)
Prerequisites: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 226 and [CISC 322 or CISC 326] and CISC 324 and [MATH 110 or MATH 111 or MATH 112]).

CISC 498 – Information Technology Project (6.00 units)
Topic selected under the supervision of a faculty member. Emphasis is on the application of software engineering techniques to the development of a substantial software system. Group work, oral presentation, participation in design and code review meetings, and delivery of complete software specification and design are required.
Learning Hours: 258 (18 Seminar, 240 Group Learning)
Prerequisites: Level 4 or above and registration in a SODE Specialization Plan and a cumulative GPA of 1.90 and a (GPA of 2.60 in CISC; COCA; COGS; SOFT) and (30.0 units in CISC; COCA; COGS; SOFT) and (a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in [CISC 322 or CISC 326] and [CISC 325 or CISC 327]).
Exclusion: CISC 496; CISC 499.

COGS 100 – Introduction to Cognitive Science (3.00 units)
A multidisciplinary approach to the study of the mind combining approached from philosophy, psychology, linguistics, neuroscience, anthropology, and artificial intelligence. Logic, rules, concepts, and other mental representations used to generate thought and behaviour. Implementation of computational and cognitive models of mental processes.
Notes: Also offered online. Consult Arts and Science Online. Learning Hours may vary.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: None.

Academic Year 2023/2024 Winter Term

This winter term period is from January 1, 2024 to April 30, 2024.

Applications for Fall/Winter term will be received until June 15, 2023.

CISC 101 – Elements of Computing Science (3.00 units)
Introduction to algorithms: their definition, design, coding, and execution on computers. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
Notes: Also offered online. Consult Arts and Science Online. Learning Hours may vary.
Sufficient preparation for CISC 121; alternative to CISC 110 and CISC 151. This course is intended for students who have no programming experience.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: None.
Exclusion: APSC 142; APSC 143; CISC 110; CISC 151.
One-Way Exclusion: May not be taken with or after CISC 121; CISC/CMPE/COCA/COGS/SOFT at the 200-level or above.

CISC 151 – Elements of Computing with Data Analytics (3.00 units)
Introduction to algorithms: their definition, design, coding, and execution on computers, with applications drawn from data analytics, including simple prediction and clustering. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
Notes: Sufficient preparation for CISC 121; alternative to CISC 101 and CISC 110.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: None.
Exclusion: APSC 142; APSC 143; CISC 101; CISC 110.
One-Way Exclusion: May not be taken with or after CISC 121; CISC/CMPE/COCA/COGS/SOFT at the 200-level or above.

CISC 226 – Game Design (3.00 units)
An introduction to techniques for designing elementary computer games. Topics will include game development tools and processes, principles of game design, game prototyping and game evaluation.
Learning Hours: 120 (36 Lecture, 60 Group Learning, 24 Private Study)
Prerequisites: Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 124.

CISC 423 – Software Requirements (3.00 units)
An integrated approach to discovering and documenting software requirements. Identification of stakeholders; customer, operator, analyst, and developer perspectives. Requirements elicitation. Transition from initial (informal) requirements to semi-formal and formal representations. Requirements analysis process; analysis patterns. Requirements specification techniques. Relation to architecture and user interface design; traceability of requirements.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 223 and CISC 235).
Corequisites: (CISC 325 and [CISC 322 or CISC 326]).

CISC 451 – Topics in Data Analytics (3.00 units)
Content will vary from year to year; typical areas covered may include: tools for large scale data analytics (Hadoop, Spark), data analytics in the cloud, properties of large scale social networks, applications of data analytics in security.
Learning Hours: 120 (36 Individual Instruction, 36 Laboratory, 48 Private Study)
Prerequisites: A minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 333 or CISC 351 or CISC 372).

CISC 458 – Programming Language Processors (S) (3.00 units)
Introduction to the systematic construction of a compiler: grammars and languages, scanners, top-down and bottom-up parsing, runtime organization, symbol tables, internal representations; Polish notation, syntax trees, semantic routines, storage allocation, code generation, interpreters.
Learning Hours: 120 (36 Lecture, 36 Laboratory, 48 Group Learning)
Prerequisites: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 121 and CISC 221 and CISC 223).

CISC 495 – Software Evolution (3.00 units)

COGS 201 – Cognition and Computation (3.00 units)
Introduction to the computational aspects of the mind. Implementation of computer programs for reasoning, decision making, and problem solving to understand these mental processes. Information theory and behaviourism; computational models of cognition, perception and memory processes demonstrating modeling approaches, and cognitive architectures.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Prerequisites: Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (COGS 100 or PSYC 100).
Exclusion: COGS 200; PSYC 220.

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Teaching Positions Available for the School of Computing – Winter 2023

Posted on 2022/11/28 by Doug Martin

The School of Computing at Queen’s University invites applications from suitably qualified candidates interested in teaching courses shown below.

Applications will be received until December 11, 2022. Review of applications will commence shortly thereafter, and the final appointment is subject to budgetary approval. Additional information about the School of Computing can be found at http://www.queensu.ca

Courses available are listed below.

To apply as a Term Adjunct, see: http://flux.cs.queensu.ca/employment/applying-for-a-term-adjunct-position/

To apply as a Teaching Fellow, see: http://flux.cs.queensu.ca/employment/applying-for-a-teaching-follow-position/

Academic Year 2022/2023 Winter Term

This winter term period is from January 1, 2023 to April 31, 2023.

Applications will be received until December 11, 2022.

CISC 423 Software Requirements Units: 3.00

An integrated approach to discovering and documenting software requirements. Identification of stakeholders; customer, operator, analyst, and developer perspectives. Requirements elicitation. Transition from initial (informal) requirements to semi-formal and formal representations. Requirements analysis process; analysis patterns. Requirements specification techniques. Relation to architecture and user interface design; traceability of requirements.
Learning Hours: 120 (36L;84P)
Prerequisite: Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 223 and CISC 235). Corequisite: (CISC 325 and [CISC 322 or CISC 326]).

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Teaching-Focused Position in Computing: Three (3) Year Term Starting July 2023

Posted on 2022/11/07 by alisa

The School of Computing in the Faculty of Arts and Science at Queen’s University invites applications for a teaching-focused 3-year non-renewable appointment at the rank of Assistant or Associate Professor that centres on computer science. The preferred start date for the appointment is July 1, 2023. Salary will be commensurate with qualifications and experience.

Candidates shall have a Ph.D. in computer science or a related discipline completed at the start date of the appointment. Post-secondary teaching, curriculum development and/or other relevant experience is required.

Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to declare their COVID-19 vaccination status and provide proof that they were fully vaccinated or had an approved accommodation to engage in in-person University activities. These requirements were suspended effective May 1, 2022, but the University may reinstate them at any point.

The main criteria for selection are demonstrated commitment to academic and teaching excellence in a post-secondary computing education environment (such as adjunct/sessional lecturing experience), and curriculum development experience. The successful candidate will be expected to demonstrate excellent teaching contributions at both the undergraduate and graduate levels. A continuing commitment to high quality scholarly work, service and administration is also expected. Support for course development and delivery as well as the scholarship of teaching and learning will be provided to the successful candidate by the Faculty of Arts and Science and through the Queen’s Centre for Teaching and Learning.

The successful candidate will be expected to:

work collaboratively in an interdisciplinary and student-focused environment;
contribute to academic and pedagogical excellence in support of the programs in the School of Computing; and
provide effective service contributions to the School, the Faculty of Arts and Science, the University, and the broader community.

The School of Computing has 35 full-time and 20 cross-appointed faculty, over 1200 undergraduate students, and over 200 graduate students. The School offers undergraduate programs in Computer Science, Software Design, Biomedical Computing, Computing and Mathematics, Computing and the Creative Arts and Cognitive Science, as well as dedicated major options in Artificial Intelligence, Biomedical Computation, Data Analytics, Fundamental Computation, Game Development, and Security. The School also offers Master’s, and Doctoral programs in Computer Science, with dedicated programs for Artificial Intelligence, Cybersecurity, Medical Informatics, and Biomedical Informatics.

People from across Canada and around the world come to learn, teach, and carry out research at Queen’s University. Faculty and their dependents are eligible for an extensive benefits package including prescription drug coverage, vision care, dental care, long term disability insurance, life insurance and access to the Employee and Family Assistance Program. You will also participate in a pension plan. Tuition assistance is available for qualifying employees, their spouses, and dependent children. Queen’s values families and is pleased to provide a ‘top up’ to government parental leave benefits for eligible employees on maternity/parental leave. In addition, Queen’s provides partial reimbursement for eligible daycare expenses for employees with dependent children in daycare. Details are set out in the Queen’s-QUFA Collective Agreement. For more information on employee benefits, see Queen’s Human Resources.

Additional information about Queen’s University can be found on the Faculty Recruitment and Support website. The University is situated on the traditional territories of the Haudenosaunee and Anishinaabe, in historic Kingston on the shores of Lake Ontario. Kingston’s residents enjoy an outstanding quality of life with a wide range of cultural, recreational, and creative opportunities. Please see Inclusive Queen’s for information on equity, diversity, and inclusion resources and initiatives.

The University invites applications from all qualified individuals. Queen’s is strongly committed to employment equity, diversity and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous/Aboriginal people, women, persons with disabilities, and 2SLGBTQ+ persons. All qualified candidates are encouraged to apply, however, in accordance with Canadian immigration requirements, Canadian citizens and permanent residents of Canada will be given priority.

To comply with federal laws, the University is obliged to gather statistical information as to how many applicants for each job vacancy are Canadian citizens / permanent residents of Canada. Applicants need not identify their country of origin or citizenship; however, all applications must include one of the following statements: “I am a Canadian citizen / permanent resident of Canada”; OR, “I am not a Canadian citizen / permanent resident of Canada”. Applications that do not include this information will be deemed incomplete.

The impact of certain circumstances that may legitimately affect a nominee’s record of research achievement will be given careful consideration when assessing the nominee’s research productivity. Candidates are encouraged to provide any relevant information about their experience and/or career interruptions.

A complete application consists of:

a cover letter (including one of the two statements regarding Canadian citizenship / permanent resident status specified above);
a current Curriculum Vitae (including a list of publications);
a statement of teaching interests and experience (including teaching outlines and evaluations if available); and
the names and contact information of three referees.

Applications should be submitted on or before December 12 2022. Applicants are encouraged to send all documents in their application packages electronically as a single PDF, Attn: Chair of Faculty Search Committee at cssearch2022@cs.queensu.ca, although hard copy applications may be submitted to:

Faculty Search Committee Chair
The School of Computing
557 Goodwin Hall
Queen’s University
Kingston, Ontario
CANADA K7L 3N6

Applicants should arrange for THREE letters of recommendation to be sent directly by their three selected referees to the Chair of Faculty Search Committee at refletter2022@cs.queensu.ca by the closing date of December 12 2022.

The University will provide support throughout the recruitment processes to applicants with disabilities, including accommodations that take into account an applicant’s accessibility needs. If you require accommodation during the interview process, please contact Robin Tippet in the School of Computing at robin.tippett@queensu.ca.

Academic staff at Queen’s University are governed by a Collective Agreement between the University and the Queen’s University Faculty Association (QUFA), which is posted on the Faculty Relations Office website.

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Teaching Assistant Positions available for Winter 2023 in the School of Computing

Posted on 2022/10/11 by Doug Martin

The Teaching Assistant Positions are available in the School of Computing for the Winter 2023.

To apply for a TA position:

Go to https://auth.caslab.queensu.ca/ta/cisc. You will be prompted by the Queen’s sign-on portal for your netid and password.
After logging on, provide your name and email to the system.
Next, go to the “TA applications” tab at the top of the page, select “Provide background”, and provide your background information. Then click “Submit” at the bottom of the page.
Finally, and only after providing your background and clicking “Submit” on that page, go to the “TA applications” tab, select “Apply”, and indicate the courses to which you are applying. Then click “Submit”.

The system will tell you when your application is complete.

Deadline is November 4, 2022. Incomplete applications will not be considered.

You must have a Canadian bank account to be hired as a TA.

For more information please contact:

Debby Robertson
Graduate Program Assistant
School of Computing
Queen’s University

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Teaching Positions Available for the School of Computing – Fall/Winter 2022-23

Posted on 2022/02/17 by Doug Martin

The School of Computing at Queen’s University invites applications from suitably qualified candidates interested in teaching courses shown below.

Applications will be received until March 31, 2022. Review of applications will commence shortly thereafter, and the final appointment is subject to budgetary approval. Additional information about the School of Computing can be found at http://www.queensu.ca

Courses available are listed below.

To apply as a Term Adjunct, see: http://flux.cs.queensu.ca/employment/applying-for-a-term-adjunct-position/

To apply as a Teaching Fellow, see: http://flux.cs.queensu.ca/employment/applying-for-a-teaching-follow-position/

Academic Year 2022/2023 Fall Term

This spring term period is from September 1, 2022 to December 31, 2022.

Applications will be received until March 31, 2022.

CISC 110 Creative Computing Units: 3.00
Introduction to fundamental programming concepts in the context of visual, interactive media. Students may develop applications in any domain (e.g., fine art, education, commerce, physical or social sciences) while learning about algorithms, program design, logic, program control flow, functions, testing, etc.
NOTE No computing or art background required.
NOTE Sufficient preparation for CISC 121/3.0. . Alternative to CISC 151/3.0. With permission of the School, students with programming experience may take this concurrently with CISC 121/3.0
LEARNING HOURS 120 (36L;84P)
Requirements: Exclusion No more than 3.0 units from APSC142;APSC143;CISC101; CISC110; CISC151. One-Way Exclusion May not be taken with or after: CISC121; CISC or SOFT at the 200 level and above.
Course Equivalencies: CISC 101/110/121 / APSC 143

CISC 121 Introduction to Computing Science I Units: 3.00
Introduction to design, analysis, and implementation of algorithms. Recursion, backtracking, and exits. Sequences. Elementary searching and sorting. Order-of-magnitude complexity. Documentation, iterative program development, translating natural language to code, testing and debugging.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P
RECOMMENDATION Some programming experience (such as high-school level programming or CISC 101/3.0 or CISC 110/3.0 or CISC 151/3.0
Requirements: Prerequisite None. Corequisite (CISC 102 or MATH 110 or MATH 111 or MATH 112 or MATH 120 or MATH 121 or MATH 123 or MATH 124 or MATH 126 or APSC 171 or APSC 172 or APSC 174 or COMM 161 or COMM 162).

CISC 235 Data Structures Units: 3.00
Design and implementation of advanced data structures and related algorithms, including correctness and complexity analysis.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 124 and CISC 203).

CISC 324 Operating Systems Units: 3.00
Layered operating systems for conventional shared memory computers: concurrent processes. Synchronization and communication. Concurrent algorithms. Scheduling. Deadlock. Memory management. Protection. File systems. Device management. Typical layers.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 221 and CISC 235).

CISC 365 Algorithms I Units: 3.00
Principles of design, analysis and implementation of efficient algorithms. Case studies from a variety of areas illustrate divide and conquer methods, the greedy approach, branch and bound algorithms and dynamic programming.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 203 and CISC 204 and CISC 235).

CISC 371 Nonlinear Data Analysis Units: 3.00
Methods for nonlinear data analysis, particularly using numerical optimization. Applications may include: unconstrained data optimization; linear equality constraints; constrained data regression; constrained data classification; evaluating the effectiveness of analysis methods.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 271 and [STAT 263 or STAT_Options]). Exclusion CISC 351.

CISC 451 Topics in Data Analytics Units: 3.00
Content will vary from year to year; typical areas covered may include: tools for large scale data analytics (Hadoop, Spark), data analytics in the cloud, properties of large scale social networks, applications of data analytics in security.
LEARNING HOURS 120 (36I;36Lb;48P)
Requirements: Prerequisite A minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 333 or CISC 351 or CISC 372).

CISC 471 Computational Biology Units: 3.00
Advanced computational approaches to the problems in molecular biology. Techniques and algorithms for sequence analysis and alignment; molecular databases; protein structure prediction and molecular data mining.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 271 and CISC 352 and CISC 365).

COGS 100 Introduction to Cognitive Science Units: 3.00
A multidisciplinary approach to the study of the mind combining approached from philosophy, psychology, linguistics, neuroscience, anthropology, and artificial intelligence. Logic, rules, concepts, and other mental representations used to generate thought and behaviour. Implementation of computational and cognitive models of mental processes.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite None.

Academic Year 2022/2023 Winter Term

This summer term period is from January 1, 2023 to April 31, 2023.

Applications will be received until March 31, 2022.

CISC 101 Elements of Computing Science Units: 3.00
Introduction to algorithms: their definition, design, coding, and execution on computers. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary. Sufficient preparation for CISC 121; alternative to CISC 110/3.0 and CISC 151/3.0
LEARNING HOURS 120(36L;84P)
Requirements: Prerequisite None. Exclusion APSC 142; APSC 143; CISC 110; CISC 151. One-Way Exclusion May not be taken with or after CISC 121; CISC at the 200-level or above.

CISC 121 Introduction to Computing Science I Units: 3.00
Introduction to design, analysis, and implementation of algorithms. Recursion, backtracking, and exits. Sequences. Elementary searching and sorting. Order-of-magnitude complexity. Documentation, iterative program development, translating natural language to code, testing and debugging.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P)
RECOMMENDATION Some programming experience (such as high-school level programming or CISC 101/3.0 or CISC 110/3.0 or CISC 151/3.0)
Requirements: Prerequisite None. Corequisite (CISC 102 or MATH 110 or MATH 111 or MATH 112 or MATH 120 or MATH 121 or MATH 123 or MATH 124 or MATH 126 or APSC 171 or APSC 172 or APSC 174 or COMM 161 or COMM 162).

CISC 151 Elements of Computing with Data Analytics Units: 3.00
Introduction to algorithms: their definition, design, coding, and execution on computers, with applications drawn from data analytics, including simple prediction and clustering. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
NOTE Sufficient preparation for CISC 121/3.0. Alternative to CISC 101/3.0 and CISC 110/3.0
LEARNING HOURS 120(36L;84P)
Requirements: excl 3 fr APSC142;CISC101, CISC110; CISC151 One-Way Exclusion May not be taken with or after CISC121; CISC or SOFT courses at the 200-level and above.

CISC 226 Game Design Units: 3.00
An introduction to techniques for designing elementary computer games. Topics will include game development tools and processes, principles of game design, game prototyping and game evaluation.
LEARNING HOURS 120 (36L;60G;24P)
Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 124.

CISC 472 Medical Informatics Units: 3.00
Current topics in the application of information technology to medical image computing and its use in image-guided medical interventions.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 330.

CISC 492 Topics in Computing III Units: 3.00
Content varies. Not offered every year.
NOTE Learning Hours will vary.
Requirements: Prerequisite Registration in a School of Computing Plan and permission of the instructor.

CISC 497 Social, Ethical and Legal Issues in Computing Units: 3.00
A wide range of topics of current importance in computing, including technical issues, professional questions, and moral and ethical decisions. Students make presentations, deliver papers, and engage in discussion.
LEARNING HOURS 120 (12L;24S;84P)
Requirements: Prerequisite Level 4 or above and registration in a COMP Major or Specialization Plan and a cumulative GPA of 1.90 and a (GPA of 2.60 in CISC; COCA; COGS; SOFT) and (30.0 units of CISC; COCA; COGS; SOFT) and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 352 or CISC 365).

COGS 201 Cognition and Computation Units: 3.00
Introduction to the computational aspects of the mind. Implementation of computer programs for reasoning, decision making, and problem solving to understand these mental processes. Information theory and behaviourism; computational models of cognition, perception and memory processes demonstrating modeling approaches, and cognitive architectures.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (COGS 100 or PSYC 100). Exclusion COGS 200; PSYC 220.

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