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--- grads:msc_student_handbook [2023/05/09 18:24] – [A. Advisory Committee Approval & Examination (Defence) Request] jhughe13
+++ grads:msc_student_handbook [2024/09/23 13:16] (current) – [A. Advisory Committee Approval & Request for Examination (Defence)] jhughe13
@@ Line 15: / Line 15: @@
 ===== Graduate Teaching Assistant (GTA) Work Assignments =====
-Many graduate students are guaranteed up to 2 GTA assignments per year in their initial offer of admission. While some graduate students may not be guaranteed GTA job assignments, all full-time, registered graduate students are eligible to apply for these positions.
+Many graduate students are guaranteed up to 2 GTA assignments per year in their initial offer of admission (Fall and Winter semesters). While some graduate students may not be guaranteed GTA job assignments, all full-time, registered graduate students are eligible to apply for these positions.
 Whether you are guaranteed GTAs or not, if you want a GTA position you must apply online each semester via [[https://www.uoguelph.ca/sessional_ta/ | GTA Work Assignments website]].
@@ Line 27: / Line 27: @@
 ===== Course Requirement =====
-An MSc student is required to take the Technical Communication and Research Methodology course [[https://calendar.uoguelph.ca/graduate-calendar/graduate-programs/computer-science/#coursestext | CIS*6890]] and at least four other CIS graduate courses [2.5 credits]. Of these four courses, at least two should be outside of the student's thesis topic area. This area and the courses which fall outside of this area are identified by the student's advisor. With approval from the Graduate Program Committee, a CIS graduate course requirement may also be met by a non-CIS graduate course or by a 4000-level course. At most one reading course (CIS*6660) and at most one 4000-level course can count towards the course requirement.
+An MSc student is required to take the Technical Communication and Research Methodology course [[https://calendar.uoguelph.ca/graduate-calendar/graduate-programs/computer-science/#coursestext | CIS*6890]] and at least four other CIS graduate courses [**2.5 credits**]. Of these four courses, at least two should be outside of the student's thesis topic area. This area and the courses which fall outside of this area are identified by the student's advisor. With approval from the Graduate Program Committee, a CIS graduate course requirement may also be met by a non-CIS graduate course or by a 4000-level course. At most one reading course (CIS*6660) and at most one 4000-level course can count towards the course requirement.
 Please refer to the Graduate Calendar for details regarding [[https://calendar.uoguelph.ca/graduate-calendar/general-regulations/academic-standings/| graduate grade interpretation]].
@@ Line 33: / Line 33: @@
 **Artificial Intelligence (AI) Collaborative Specialization**
-An MSc student enrolled in the [[https://calendar.uoguelph.ca/graduate-calendar/collaborative-specializations/artificial-intelligence/#requirementstext| AI Collaborative Specialization]] is required to take five and a half courses [2.75 credits] from the following below:
+An MSc student enrolled in the [[https://calendar.uoguelph.ca/graduate-calendar/collaborative-specializations/artificial-intelligence/#requirementstext| AI Collaborative Specialization]] is required to take five and a half courses [**2.75 credits**] from the following below:
+[[https://www.uoguelph.ca/ceps/system/files/2023%20Collaborative%20Specialization%20in%20Artificial%20Intelligence%20Program%20Course%20Requirements.pdf | AI Collaborative Specialization Course Requirements Chart]]
 Compulsory Courses [1.25 credits]:
@@ Line 47: / Line 49: @@
 Courses [1.00 credits] from the following Complementary AI-related courses:
-  * BINF*6970 Statistical Bioinformatics
-  * CIS*6050 Neural Networks
+  *     BINF*6970 Statistical Bioinformatics
-  * CIS*6060 Bioinformatics
+  *     CIS*6050 Neural Networks
-  * CIS*6070 Discrete Optimization
+  *     CIS*6060 Bioinformatics
-  * CIS*6080 Genetic Algorithms
+  *     CIS*6070 Discrete Optimization
-  * CIS*6120 Uncertainty Reasoning in Knowledge Representation
+  *     CIS*6080 Genetic Algorithms
-  * CIS*6160 Multiagent Systems
+  *     CIS*6120 Uncertainty Reasoning in Knowledge Representation
-  * CIS*6170 Human-Computer Interaction
+  *     CIS*6160 Multiagent Systems
-  * CIS*6180/DATA*6300 Analysis of Big Data
+  *     CIS*6170 Human-Computer Interaction
-  * CIS*6190/DATA*6400 Machine Learning for Sequential Data Processing
+  *     CIS*6180/DATA*6300 Analysis of Big Data
-  * CIS*6320 Image Processing Algorithms and Applications
+  *     CIS*6190/DATA*6400 Machine Learning for Sequential Data Processing
-  * CIS*6420 Soft Computing
+  *     CIS*6320 Image Processing Algorithms and Applications
-  * ENGG*4460 Robotic Systems
+  *     CIS*6420 Soft Computing
-  * ENGG*6090 Image Analysis
+  *     ENGG*4460 Robotic Systems
-  * ENGG*6100 Machine Vision
+  *     ENGG*6090 Image Analysis
-  * ENGG*6140 Optimization Techniques for Engineering
+  *     ENGG*6100 Machine Vision
-  * ENGG*6570 Advanced Soft Computing
+  *     ENGG*6140 Optimization Techniques for Engineering
-  * MATH*6020 Scientific Computing
+  *     ENGG*6570 Advanced Soft Computing
-  * MATH*6021 Optimization I
+  *     ENGG*6600 Reinforcement Learning *Fall 2022 offering only
-  * MATH*6051 Mathematical Modelling
+  *     MATH*6020 Scientific Computing
-  * PHIL*6400 Ethics of Data Science (formerly PHIL*6760 Science and Ethics)
+  *     MATH*6021 Optimization I
-  * STAT*4000 Statistical Computing
+  *     MATH*6051 Mathematical Modelling
-  * STAT*6721 Stochastic Modelling
+  *     PHIL*6400 Ethics of Data Science (formerly PHIL*6760 Science and Ethics)
-  * STAT*6821 Multivariate Analysis
+  *     STAT*4000 Statistical Computing
-  * STAT*6841 Computational Statistical Inference
+  *     STAT*6721 Stochastic Modelling
+  *     STAT*6821 Multivariate Analysis
+  *     STAT*6841 Computational Statistical Inference
+//
+Note: CSAI students can elect to take a second "elective core course" in lieu of a complementary AI-related course.//
 **One Health Collaborative Specialization**
-An MSc student enrolled in the [[https://calendar.uoguelph.ca/graduate-calendar/collaborative-specializations/one-health/#coursestext| One Health Collaborative Specialization]] is required to take six grad courses from the following below [3.0 credits]:
+An MSc student enrolled in the [[https://calendar.uoguelph.ca/graduate-calendar/collaborative-specializations/one-health/#coursestext| One Health Collaborative Specialization]] is required to take six grad courses from the following below [**2.5 credits**]:
   * CIS*6890 Technical Communication and Research Methodology [0.5]
   * ONEH*6000 One Health Approaches to Research [0.5]
   * ONEH*6100 Master’s Seminar in One Health [0.5]
-  * 3x 0.5 Computer Science graduate courses [1.5]
+  * 2x 0.5 Computer Science graduate courses [1.00]
 ----
@@ Line 140: / Line 146: @@
   *   [[https://www.uoguelph.ca/graduatestudies/sites/uoguelph.ca.graduatestudies/files/exam_request%20a.pdf | Examination Request Form]]
-  *   {{ :grads:grad_faculty_nomination_form_-_w23.pdf | Exam Committee - Graduate Faculty Nomination}}
+  * {{ :grads:grad_faculty_nomination_form_-_f24.pdf | Graduate Faculty Nomination [Exam Committee]}}
   *   Tentative date range for the defence
+  *   Mode of delivery: Students have the option of conducting defences online or in-person
 ==== B. TurnItIn ====
-All students are required to upload their final draft thesis to [[http://turnitin.com/| TurnItIn]]. Students must register using their @uoguelph.ca email address (all others will be deleted). The 'course' you should register in is called **"Graduate Research 2022-2023"**.  The class id and enrollment password are:
+All graduate students have access to [[http://turnitin.com/| TurnItIn]], whereby students can upload their thesis drafts for instant plagiarism analysis. Students must register using their @uoguelph.ca email address (all others will be deleted). The 'course' you should register in is called **"Graduate Research 2024-2025"**.  The class id and enrollment password are:
-  * Class ID: 37150135
+  * Class ID: 41253109
   * Enrollment password: SoCSRules
-The thesis that is uploaded to Turnitin will be the version that the Graduate Program Assistant sends to the Examination Committee for final review.
 ==== D.  Examination Committee ====
-Preparations to begin forming the Examination Committee for the MSc Defence will begin once the Examination Request, Graduate Faculty Nominations and target defence dates have been submitted to the GPA. The student's advisor is responsible for assisting the student with selecting the graduate faculty nominations, and these should be completed using the Graduate Faculty Nomination form. In addition, the student must have the final draft version of their thesis uploaded to [[http://turnitin.com/| TurnItIn]], or emailed directly to the GPA.
+Preparations to begin forming the Examination Committee for the MSc Defence will begin once the Examination Request, Graduate Faculty Nominations and target defence dates have been submitted to the GPA. The student's advisor is responsible for assisting the student with selecting the graduate faculty nominations, and these should be completed using the Graduate Faculty Nomination form.
-The GPA will work with the Graduate Progress Committee to establish and approved the proposed Examination Committee. Once the Examination Committee is formed, the examination will be officially scheduled.
+The GPA will work with the Graduate Progress Committee to establish and approved the Examination Committee. Once the Examination Committee is formed, the examination will be officially scheduled.
-Please note: Members of the Examination Committee will require a minimum of 2 weeks to review the thesis prior to the defence.
+The candidate must have the final version of their thesis submitted directly to the GPA via email (this will be the version of the thesis shared with the Examination Committee). **The Examination Committee requires at least 2 weeks to review the thesis prior to the scheduled oral defence**.
 **For detailed information on Examination Committees, please refer to {{ :grads:msc_graduate_committees_.pdf |MSc Graduate Committees}}**
+SoCS follows the [[https://calendar.uoguelph.ca/graduate-calendar/degree-regulations/masters-degree-thesis/ |Office of Graduate and Postdoctoral Studies thesis guidelines]] for MSc Defences.
 ==== E. Notification of Defence ====
-Notice of the defence will be sent by the Graduate Program Assistant to the SoCS Faculty & current Graduate Students, posted on the SoCS web site, the News & Announcement section of the SoCS website homepage and advertised on the graduate bulletin board.
+Notice of the defence will be sent by the GPA (at least one week prior) to the SoCS Faculty & Graduate Students email listserv and advertised on the News & Announcement section of the [[https://www.uoguelph.ca/computing | SoCS website.]]
 ==== F.  Thesis Completion ====