Advice for Students completing the B.S. degree in Computer Science based on Quarters How to Satisfy Computer Science Related Electives

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1 Advice for Students completing the B.S. degree in Computer Science based on Quarters How to Satisfy Computer Science Related Electives Students completing their B.S. degree under quarters had a requirement that included taking a minimum of 24 credit hours (in most cases this equated to six courses) of computer science electives. Within this category, at least two of the chosen computer science electives had to be considered related. The Undergraduate Advising Handbook provided lists of courses that were considered related and students could inquire whether courses not found in any of the lists were considered related or not. In creating the new semester-based version of the B.S. degree in Computer Science, several things took place with regards to computer science electives that affect students under the older quarter-based program. Now under semesters, computer science electives belong to one or more groupings called clusters. These clusters apply to both undergraduate- and graduate-level courses and undergraduate students with the proper prerequisites are permitted and encouraged to take graduate-level Computer Science courses. Students should note, however, that in some cases, a graduate-level course should not be selected if the student has completed a similar undergraduate-level course. Such details may be found in the course catalog description. Students completing their B.S. degree in Computer Science under quarters should seek to take two computer science electives from the same cluster as a way of completing the requirement that two of their electives be considered Computer Science Related Electives. The following charts display undergraduate- and graduate-level Computer Science courses defined under semesters and what clusters they fit into. If a student previously took one course under quarters that was mapped into a semester course, we will count that course as related to one of the other courses now categorized as belonging to the same cluster. For example, a student under quarters who previously took (Database Concepts) as a CS elective could count that course along with CSCI 420 (Principles of Data Mining) as their two Computer Science Related Electives. (If they had taken previously, then they would not take CSCI 320 now since CSCI 320 is considered the semester equivalent to This kind of information is found elsewhere.) There are some additional complications. Some Computer Science courses under quarters were not converted to semesters; some courses were merged together to form new courses; and some courses that used to be electives are now required. Note that Seminar and Topic course numbers are generic; individual instances of specific Seminar and Topic course numbers will indicate which specific clusters, if any, are associated with each specific instance. For example, CSCI 759 (Topics in ) is a generic course number that covers courses that might fit into some combination of the AOS, DSS, or SEC clusters. CSCI 729 (Topics in Pervasive and Mobile ) was a specific instance of this course number that was created and this specific instance was classified as only belonging to the DSS (or Distributed ) cluster. We cannot cover all of the possibilities so students are encouraged to consult their academic

2 advisor to confirm that choices they intend to make will count as Computer Science Related Electives. We do provide a table here that identifies selected semester-based courses and clusters we identify these courses with for students following the B.S. degree under quarters (the courses listed in this first table represent courses that are now required for students following the B.S. degree under semesters and which may or may not have existed under quarters). Guide to Computer Science Electives and Associated s Undergraduate Names 243 The Mechanics of Programming 251 Concepts of Parallel and Distributed 261 Analysis of Algorithms 264 Honors Analysis of Algorithms 320 Principles of Data Management 331 Intelligent Guide to Computer Science Electives and Associated s Undergraduate Names 351 Data Communications and Networks 352 Operating 420 Principles of Data Mining 431 Introduction to Computer Vision 452 Programming 453 Computer Architecture 455 Principles of Computer Security 462 Introduction to Cryptography 464 Treme Theory 509 Seminar in Computer Science (no cluster associated with this course)

3 510 Introduction to Computer Graphics 519 Seminar in Computer Graphics 529 Seminar in Data Management 531 Introduction to Security Measurement 532 Introduction to Intelligent Security 539 Seminar in Intelligent 541 Programming Skills 549 Seminar in Languages and Tools 559 Seminar in 569 Seminar in Theory 599 Computer Science Undergraduate Independent Study (*) Guide to Computer Science Electives and Associated s Graduate Names 610 Foundations of Computer Graphics 620 Introduction to Big Data 621 Database System Implementation 622 Data Security and Privacy 630 Foundations of Intelligent 631 Foundations of Computer Vision 632 Mobile Robot Programming 633 Biologically Inspired Intelligent 641 Advanced Programming Skills 642 Secure Coding 651 Foundations of Computer Networks

4 652 Distributed 654 Foundations of Parallel Computing 661 Foundations of Computer Science Theory 662 Foundations of Cryptography 664 Computational Complexity 665 Foundations of Algorithms 687 Graduate Research Seminar (no cluster associated with this course) 709 Topics in Computer Science (no cluster associated with this course) 711 Global Illumination 712 Computer Animation: Algorithms and Techniques 713 Applied Perception in Graphics and Visualization 714 Scientific Visualization 715 Applications in Virtual Reality 716 Computational Geometry 719 Topics in Computer Graphics 720 Big Data Analytics 721 Data Cleaning and Preparation 729 Topics in Data Management 731 Advanced Computer Vision 732 Image Understanding 734 Foundations of Security Measurement and Evaluation 735 Foundations of Intelligent Security 736 Neural Networks and Machine Learning 737 Pattern Recognition 739 Topics in Intelligent 740 Programming Language Theory 742 Compiler Construction 746 Software Development Tools 749 Topics in Languages and Tools 759 Topics in

5 761 Topics in Advanced Algorithms 762 Advanced Cryptography 769 Topics in Theory 799 Computer Science Graduate Independent Study (*) (*) Independent study projects are proposed by a student working in conjunction with a faculty member who agrees to sponsor the project. The proposal form offers the student and faculty member a chance to propose that the project be associated with a specific cluster the proposed cluster designation is reviewed by the coordinators when the proposal form is submitted. Approval of the independent study project includes approval of the proposed cluster designation. Guide to Computer Science s AOS Architecture and Operating CGV Computer Graphics and Visualization DMT Data Management DSS Distributed ISS Intelligent LTS Languages and Tools SEC Security THR Theory Partial Guide to RIT ing Scheme Range Interpretation Introductory lower-division undergraduate courses Lower-division undergraduate courses Upper-division undergraduate courses Advanced upper-division undergraduate courses Introductory graduate courses Advanced graduate courses

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