SSP

The Computing, Mathematics, and Analytics Specialization is intended for students aiming at graduate work in the theory of Computing or in an applied area of Computing that requires significant mathematical expertise, such as communications, optimization, security, or biomedical computing. This program will give students a potent combination of Computer Science and Mathematics as it relates to research in Computing, and will prepare graduates well for advanced degrees or careers in a variety of areas in industry.

The plan is primarily intended for students aiming at graduate work in the theory of Computing or in an applied area of Computing requiring significant mathematical expertise, such as communications, optimization, security, or biomedical computing. The plan will give such students a solid Computing background and a good foundation in Mathematics relevant to Computing, and provides a suitable balance between research-oriented Computing and relevant pure and applied Mathematics.

The primary objective of the program is to prepare students aiming for graduate work in Computing with solid foundations in Computing and in Mathematics relevant to Computing. Another career path would be to the software industry; graduates of Computing programs are currently in great demand. The mathematical knowledge gained through this program will provide a significant advantage in competing for research-oriented positions in high-tech industries. Finally, given the demand for teachers in both Computing, Mathematics, and Analytics, Computing, Mathematics, and Analytics may be of interest to those considering Concurrent Education at Queen's.

What follows is a list of the required unit credits for the Computing, Mathematics, and Analytics program. This information is meant as a guide and is subject to change. The precise and up-to-date requirements for Computing degree plans can be found online in the Arts and Science Calendar. In case of discrepancies, the calendar should be considered as the official definition.

Typical 4-years honours programs consist of 120 unit credits. A one-term course is worth 3 units, while a full year (two-term) course is worth 6 units. All courses listed below are 3 units unless specified with a /6.0 after the course code.

- CISC 121 Introduction to Computing Science I
- CISC 124 Introduction to Computing Science II
*One of the following Linear Algebra options:*- MATH 110/6.0 Linear Algebra
- MATH 111/6.0 Linear Algebra

*and*

CISC 102 Discrete Mathematics for Computing Science I

*One of the following Calculus options:*- MATH 120/6.0 Differential and Integral Calculus
- MATH 121/6.0 Differential and Integral Calculus
- MATH 123 Differential and Integral Calculus I

*and*

MATH 124 Differential and Integral Calculus II

- CISC 203 Discrete Mathematics for Computing Science II
- CISC 204 Logic for Computing Science
- CISC 221 Computer Architecture
- CISC 223 Software Specifications
- CISC 235 Information Structures
- STAT 269 Statistics and Probability II
*One of the following courses:*- CISC 322 Software Architecture
- CISC 326 Game Architecture

- CISC 324 Operating Systems
- CISC 360 Programming Paradigms
- CISC 365 Algorithms I
- STAT 361 Applied Methods in Statistics I
- CISC 497 Social, Ethical and Legal Issues in Computing
- STAT 463 Fundamentals of Statistical Inference
*One of the following 2 options:**Two of the following courses:*- MATH 210 Rings and Fields
- MATH 310 Group Theory
- MATH 311 Elementary Number Theory
- MATH 413 Introduction to Algebraic Geometry
- MATH 414 Introduction to Galois Theory

- MATH 211/6.0 Algebraic Methods

*One of the following 2 courses:*- MATH 221 Vector Calculus
- MATH 280 Advanced Calculus

*One of the following 2 courses:*- STAT 268 Statistics and Probability I
- STAT 351 Probability I

*12 units from the following:*- CISC 271 Linear Data Analysis
- BIOM 300 Modeling Techniques in Biology
- CISC 330 Computer-Integrated Surgery
- CISC 371 Nonlinear Data Analysis
- CISC 372 Advanced Data Analytics
- MATH 337 Introduction to Operations Research Models
- MATH 339 Evolutionary Game Theory
- STAT 361 Applied Methods in Statistics I
- CISC 422 Formal Methods in Software Engineering
- CISC 457 Image Processing and Computer Vision
- CISC 462 Computability and Complexity
- CISC 465 Semantics of Programming Languages
- CISC 466 Algorithms II
- CISC 467 Fuzzy Logic
- CISC 472 Medical Informatics
- CISC 473 Deep Learning
- MATH 401 Graph Theory
- MATH 402 Enumerative Combinatorics
- MATH 406 Introduction to Coding Theory
- MATH 413 Introduction to Algebraic Geometry
- MATH 414 Introduction to Galois Theory
- MATH 418 Number Theory and Cryptography
- MATH 474 Information Theory
- MATH 477 Data Compression and Source Coding
- STAT 456 Bayesian Analysis
- STAT 457 Statistical Computing
- STAT 462 Computational Data Analysis
- STAT 463 Fundamentals of Statistical Inference
- STAT 464 Discrete Time Series Analysis
- STAT 471 Sampling and Experimental Design
- STAT 473 Generalized Linear Models
- STAT 486 Survival Analysis
- CISC 500/6.0 Undergraduate Thesis

*One of the following project courses:*- CISC 499 Advanced Undergraduate Project
- CISC 500/6.0 Advanced Research Project

Admission to a degree program in the Faculty of Arts and Science from an Ontario Secondary School is based on the completion of the Ontario Secondary School Diploma (OSSD). Please see Admissions for details.

Apply at the Ontario Universities Application Centre using the program code QD (Queen's University, Computing) or QG (Queen's University, Concurrent Education with Computing).

More information may be obtained by sending mail to undergrad@cs.queensu.ca or by contacting the Computing, Mathematics, and Analytics advisor: