Mathematics
Mathematics and statistics are not only powerful problem-solving tools, but also highly creative fields of studies that combine imagination with logic, and precision with intuition.
Mathematics is much more than numbers! Its basic goal is to reveal and model general patterns to help explain our world, whether they be found in electrical impulses in the human nervous system, the evolution of animal populations in their habitats, fluctuations in stock-market prices, or electronic communications. Mathematics reaches far beyond science and engineering into medicine, business and the social sciences.
Advances in mathematics and statistics lie behind many discoveries that are now part of our daily lives, such as MRI scanners, digital compression of music and video, secure electronic communications, data mining, genomic algorithms, futures pricing, and many other innovations.
The Department of Mathematics and Statistics offers Honours, majors and minors both in mathematics and in statistics. Our Honours program in statistics is accredited by the Statistical Society of Canada, allowing graduates to earn the A.Stat. professional designation. Moreover, the Department offers a joint honours program in mathematics and economics, a joint honours program in mathematics and computer science, as well as a multidisciplinary program in financial mathematics and economics. All our honours programs also include the co-operative education option.
Computer Science
Computer science at the School of Electrical Engineering and Computer Science combines the study of computation and information processing fundamentals with their application in the world around us. Computer scientists build fast, reliable, scalable and secure software systems to organize and analyze information. The honours curriculum comprises advanced topics in databases, artificial intelligence, computer graphics, security, distributed computing and algorithm design, culminating in an honours project.
This program teaches graduates how to use their creative and innovative talents to conceive, design and implement software systems. The French Immersion Stream is now available to all students in the Computer Science program. Our degrees are very flexible and include options, minors and a major, which can be used to explore connections between computer science and many other fields of study.
Co-operative education is available with this program.
The French immersion stream is available with this program.
Requirements for this program have been modified. Please consult the 2022-2023 calendars for the previous requirements.
Code | Title | Units |
---|---|---|
Compulsory courses at the 1000 level: | ||
ENG 1112 | Technical Report Writing | 3 Units |
ITI 1100 | Digital Systems I | 3 Units |
ITI 1120 | Introduction to Computing I | 3 Units |
ITI 1121 | Introduction to Computing II | 3 Units |
MAT 1320 | Calculus I | 3 Units |
MAT 1322 | Calculus II | 3 Units |
MAT 1341 | Introduction to Linear Algebra | 3 Units |
MAT 1348 | Discrete Mathematics for Computing | 3 Units |
Compulsory courses at the 2000 level: | ||
CEG 2136 | Computer Architecture I | 3 Units |
CSI 2101 | Discrete Structures | 3 Units |
CSI 2110 | Data Structures and Algorithms | 3 Units |
CSI 2120 | Programming Paradigms | 3 Units |
CSI 2132 | Databases I | 3 Units |
CSI 2911 | Professional Practice in Computing | 3 Units |
MAT 2122 | Multivariable Calculus | 3 Units |
MAT 2125 | Elementary Real Analysis | 3 Units |
MAT 2143 | Introduction to Group Theory | 3 Units |
MAT 2371 | Introduction to Probability | 3 Units |
MAT 2375 | Introduction to Statistics | 3 Units |
SEG 2105 | Introduction to Software Engineering | 3 Units |
Compulsory courses at the 3000 level: | ||
CSI 3104 | Introduction to Formal Languages | 3 Units |
CSI 3105 | Design and Analysis of Algorithms I | 3 Units |
CSI 3120 | Programming Language Concepts | 3 Units |
CSI 3131 | Operating Systems | 3 Units |
MAT 3341 | Applied Linear Algebra | 3 Units |
MAT 3373 | Methods of Machine Learning | 3 Units |
MAT 3375 | Regression Analysis | 3 Units |
SDS 3386 | Data Science Lab | 3 Units |
Compulsory courses at the 4000 level: | ||
CSI 4106 | Introduction to Artificial Intelligence | 3 Units |
CSI 4142 | Fundamentals of Data Science | 3 Units |
MAT 4374 | Computational Statistics | 3 Units |
MAT 4376 | Topics in Statistics | 3 Units |
Optional Courses | ||
3 optional course units from: | 3 Units | |
Honours Linear Algebra | ||
Introduction to Applied Linear Algebra | ||
3 optional course units from: | 3 Units | |
Machine Learning | ||
Statistical Machine Learning | ||
3 optional course units from: | 3 Units | |
Honours Project | ||
Undergraduate Research Project | ||
9 optional course units from: | 9 Units | |
Sampling and Surveys | ||
Analysis of Experimental Designs | ||
Introduction to Time Series Analysis | ||
Multivariate Statistical Methods | ||
Optimization: Theory and Practice | ||
9 optional course units from: | 9 Units | |
Introduction to Data Communications and Networking | ||
Databases II | ||
WWW Structures, Techniques and Standards | ||
Information Retrieval and the Internet | ||
Design of Secure Computer Systems | ||
Computer Graphics | ||
6 optional course units in mathematics (MAT) or computer science (CSI) at the 3000 or 4000 level | 6 Units | |
6 optional course units in computer science (CSI) at the 2000 or 3000 or 4000 level | 6 Units | |
6 optional course units in mathematics (MAT) at the 2000 or 3000 or 4000 level | 6 Units | |
9 elective course units offered by the University of Ottawa excluding courses offered by the Faculty of Science and the Faculty of Engineering | 9 Units | |
Total: | 150 Units |