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Course Lists

Computer science graduate studies students working in the VR lab.
Course
Course Name & Decription
Professor
Schedule Location
CP8101
 
Research Methods for Doctoral Students
This course is designed to assist students in developing skills necessary to design and execute a research protocol for their terminal degree. The course is intended to complement the specific research programs devised by the student and his/her advisors. The course covers the following topics: nature of scientific inquiry, library skills, formulation and testing of hypotheses, experimental design, statistical analysis of data, human subjects, use of humans and animals in research, and professional responsibility in research grants and funding for research. Pass/Fail
Dr. C. Ding Wednesday
15:00-18:00
VIC101
CP8201 Advanced Algorithms
This course covers advanced methods of algorithmic design and analysis with focus on efficiency and correctness of algorithms. The course reviews several popular algorithm design techniques and selected well-known algorithms. The final parts of the course include introduction to practical algorithms for computationally challenging problems, using heuristics, approximation algorithms and introduction to randomization algorithms. 1 Credit  
M. Soutchanski Tuesday
13:00-15:00

TRS-3147

 

Thursday
15:00-16:00
TRS-3149
CP8215* Research Methods in Computer Science
A transition to research-based learning for computer science students designed to assist them in developing a research protocol. The course complements specific research programs devised by the students and their supervisors. Topics may include: the nature of scientific inquiry; information gathering skills; formulation and testing of hypotheses; experimental design; planning; analysis of data; ethical and professional responsibility in research. 1 Credit
Not available to Course option students. Only one of CP8310 and CP8215 may be taken for credit toward degree completion.  
Dr. C. Ding Wednesday
15:00-18:00
VIC101
CP8309
Section 1
Special Topics: Emerging Computer Science
This special topics course examines selected, advanced topics in areas related to emerging areas of computer science
that are not covered by existing courses. The topic(s) will vary depending on the need and the instructor. 1 Credit
Topics for Fall 2019:
Section 1: Neural Information Processing: Computational solutions to perception with a heavy emphasis on deep learning and vision. This includes solutions to achieving artificial vision in computer systems or robots, understanding human vision at a computational level of abstraction, and relationships between these topics. Other sensory modalities (e.g. audition) will receive some treatment at a coarse-grained level of specificity. The core of the course appeals to characteristics of neural information processing viewed through formalisms including information theory, compressive sensing and especially parallels between neural networks in artificial and biological nervous systems.  
Dr. N. Bruce Friday
12:00-15:00
VIC-110
CP8309
Section 2
Special Topics: Emerging Computer Science
This special topics course examines selected, advanced topics in areas related to emerging areas of computer science
that are not covered by existing courses. The topic(s) will vary depending on the need and the instructor. 1 Credit
Topics for Fall 2019:
Section 2: Natural Language Processing: Natural Language Processing addresses fundamental questions at the intersection of human languages and computer science. How can computers acquire, comprehend and produce human languages? How can computational methods give us insight into observed human language phenomena? In this advanced NLP course, the students will learn how computers can deal with human languages.
This course will prepare students for graduate-level research in advanced natural language processing, and give them the background to qualify for job opportunities in this field in industry. It will also be useful for students interested in working in other fields (i.e. Artificial Intelligence, Data Mining, Information Retrieval) from a computational science perspective.  
Dr. V. Hu Friday
09:00-12:00
VIC-304
CP8310* Directed Studies in Computer Science
This course is for Master’s students who wish to gain knowledge in a specific area for which no graduate level classes are offered. Students wishing to take the class would be assigned a suitable class advisor most familiar with the specific area of interest. Students are required to present the work of one term (not less than 90 hours in the form of directed research, tutorials and individual study) in an organized format. 1 Credit
Not available to Course option students. Only one of CP8310 and CP8215 may be taken for credit toward degree completion.
N/A N/A N/A
CP8312* Directed Studies: Intelligence and Robotics
This course explores theoretical, practical and experimental (if applicable) problems in great depth in the areas of intelligence and robotics with emphasis on the aspects of Intelligence and Robotics and their application related to the discipline of Computer Science. Doctoral students must present their findings in a formal report. 1 Credit.  
N/A N/A N/A
CP8313* Directed Studies: Networks
This course explores theoretical, practical and experimental (if applicable) problems in great depth in areas of computer and communication networks with emphasis on the aspects of computer networking and its application related to the discipline of Computer Science. Doctoral students must present the findings in a formal report. 1 Credit  
N/A N/A N/A
CP8315
Section 1
Special Doctoral Topics: AI & Robotics
This special topics course will present material that is not currently part of the regular computer science doctoral program but are of interest to faculty and students in the field of Artificial Intelligence and Robotics. 1 Credit
Topics for Fall 2019:
Section 1: Neural Information Processing: Computational solutions to perception with a heavy emphasis on deep learning and vision. This includes solutions to achieving artificial vision in computer systems or robots, understanding human vision at a computational level of abstraction, and relationships between these topics. Other sensory modalities (e.g. audition) will receive some treatment at a coarse-grained level of specificity. The core of the course appeals to characteristics of neural information processing viewed through formalisms including information theory, compressive sensing and especially parallels between neural networks in artificial and biological nervous systems.  
Dr. N. Bruce Friday
12:00-15:00
VIC-110
CP8315
Section 2
Special Doctoral Topics: AI & Robotics
This special topics course will present material that is not currently part of the regular computer science doctoral program but are of interest to faculty and students in the field of Artificial Intelligence and Robotics. 1 Credit
Topics for Fall 2019:
Section 2: Natural Language Processing: Natural Language Processing addresses fundamental questions at the intersection of human languages and computer science. How can computers acquire, comprehend and produce human languages? How can computational methods give us insight into observed human language phenomena? In this advanced NLP course, the students will learn how computers can deal with human languages. This course will prepare students for graduate-level research in advanced natural language processing, and give them the background to qualify for job opportunities in this field in industry. It will also be useful for students interested in working in other fields (i.e. Artificial Intelligence, Data Mining, Information Retrieval) from a computational science perspective.  
Dr. V. Hu Friday
09:00-12:00
VIC-304
CP8318 Machine Learning
Machine learning is the study of algorithms that learn to perform a task from prior experience. Machine learning has a broad range of applicability, including computer vision, robotics, medical diagnosis, bioinformatics and natural language processing. This course will cover the underlying theory and practical applications of machine learning. 1 Credit.  
Dr. N. Bruce Wednesday
10:00-13:00
TRS-2166
CP8320 Program Analysis for Cyber Security
This course will focus on Language-Based Security, an area of research that studies how to enforce application-level security using program analysis techniques. This includes techniques used to automate the detection\prevention of security vulnerabilities caused by coding malpractice or security-policy misconfigurations; the study of the design and implementation of secure programming languages; and techniques used to enforce correct usage of security Application Programming Interfaces. 1 Credit.  
Dr. M. Alalfi Thursday
09:00-12:00
VIC-110
CP9102* Doctoral Seminar
The purpose of the Doctoral Seminar is to provide students exposure to the latest research, issues and findings related to the discipline of Computer Science. The seminar will consist of invited guests and talks by experts from industry, academia and graduate students themselves. Students will have an opportunity to improve their writing and critical thinking skills through assigned work associated with the seminar topics. All students are required to attend and actively participate in seminars every semester for a total of six semesters. A doctoral candidate must give two publicly announced research seminars on his/her thesis research. The student's supervisor(s) and at least one other member of the student's Dissertation Supervisory Committee must attend this seminar. The quality of the student's presentation will be graded on a Pass/Fail basis. Each student will be required to pass each research seminar presentation. Pass/Fail.  
Dr. J. Misic Monday
12:00-13:00
NG-LG24

* Requires a PDF fileDirected Studies / Restricted Courses Request Form for enrollment.

1. Fall classes begin Tuesday, September 3, 2019.
2. Refer to the Significant Dates for course ADD and DROP deadlines
3. See the Graduate Calendar for Program Curriculum and Course Descriptions

Course
Course Name & Description
Professor Schedule Location
CP8202 Advanced Software Engineering
Modern approaches to software development are studied including requirements analysis, system design techniques, formal description techniques, implementation, testing, debugging, metrics, human factors, quality assurance, cost estimation, maintenance, and tools. 1 Credit
Dr. V. Misic TBA TBA
CP8210 Topics in Data Science
This course presents concepts related to data science research activities including data management and analytics, data modeling, structured and unstructured data, regression models, social data analysis, web and data mining, information retrieval, text analysis and natural language processing. 1 Credit
Dr. A. Abhari TBA TBA
CP8301 Secure Computing
The importance of security for computer systems: protection, access control, distributed access control, Unix security, applied cryptography, network security, firewalls, secure coding practices, safe languages, mobile code. Computer and network forensics techniques. Computer security techniques. Legal and Ethical issues. Topics may include cryptographic protocols, privacy, anonymity, and/or other topics as time permits. 1 Credit
Dr. A. Miri TBA TBA
CP8302 Software Metrics
The theory of measurement, experimental design, software metrics collection, statistics for analyzing measurement data, software size and software structure, resource measurement, prediction of software characteristics, planning software measurement, software quality and reliability. 1 Credit
Dr. A. Miranskyy TBA TBA
CP8307 Introduction to Computer Vision
This course describes foundational concepts of computer vision. In particular, the course covers the image formation process, image representation, feature extraction, model fitting, motion analysis, 3D parameter estimation and applications. 1 Credit
Dr. K. Derpanis TBA TBA
CP8309 Special Topics: Emerging Computer Science
This special topics course examines selected, advanced topics in areas related to emerging areas of computer science
that are not covered by existing courses. The topic(s) will vary depending on the need and the instructor. 1 Credit
Dr. J. Misic TBA TBA
CP8310* Directed Studies in Computer Science
This course is for Master’s students who wish to gain knowledge in a specific area for which no graduate level classes are offered. Students wishing to take the class would be assigned a suitable class advisor most familiar with the specific area of interest. Students are required to present the work of one term (not less than 90 hours in the form of directed research, tutorials and individual study) in an organized format. 1 Credit Not available to Course option students. Only one of CP8310 and CP8215 may be taken for credit toward degree completion.
N/A N/A  
CP8312* Directed Studies: Intelligence and Robotics
This course explores theoretical, practical and experimental (if applicable) problems in great depth in the areas of intelligence and robotics with emphasis on the aspects of Intelligence and Robotics and their application related to the discipline of Computer Science. Doctoral students must present their findings in a formal report. 1 Credit.
N/A N/A  
CP8313* Directed Studies: Networks
This course explores theoretical, practical and experimental (if applicable) problems in great depth in areas of computer and
communication networks with emphasis on the aspects of computer networking and its application related to the discipline of Computer Science. Doctoral students must present the findings in a formal report. 1 Credit
N/A N/A  
CP8314 Advanced Artificial Intelligence
The course will focus on the theory and implementation of dynamical systems from the perspective of artificial intelligence. The emphasis will be on the compromises involved in providing useful logical representations that allow reasoning about actions to remain tractable. The course will show how these research issues are relevant for many applications beyond the traditional area of artificial intelligence. 1 Credit
Dr. M. Soutchanski TBA TBA
CP8316 Special Doctoral Topics: Networks
This special topics course will present material that is not currently part of the regular computer science doctoral program but are of interest to faculty and students in the field of Networking. 1 Credit
Dr. J. Misic TBA TBA
CP9102* Doctoral Seminar
The purpose of the Doctoral Seminar is to provide students exposure to the latest research, issues and findings related to the discipline of Computer Science. The seminar will consist of invited guests and talks by experts from industry, academia and graduate students themselves. Students will have an opportunity to improve their writing and critical thinking skills through assigned work associated with the seminar topics. All students are required to attend and actively participate in seminars every semester for a total of six semesters. A doctoral candidate must give two publicly announced research seminars on his/her thesis research. The student's supervisor(s) and at least one other member of the student's Dissertation Supervisory Committee must attend this seminar. The quality of the student's presentation will be graded on a Pass/Fail basis. Each student will be required to pass each research seminar presentation. Pass/Fail.
Dr. I. Woungang TBA TBA

* Requires a PDF fileDirected Studies / Restricted Courses Request Form for enrollment.

Notes:
1. Winter classes begin Friday, January 10, 2020.
2. Refer to the Significant Dates for course ADD and DROP deadlines.
3. See the Graduate Calendar for Program Curriculum and Course Descriptions.