Computer Science Courses Computer Science 1 This Course Is .
Computer ScienceCOMPUTER SCIENCEComputer Science CoursesC S 111. Computer Science Principles4 Credits (3 2P)This course provides a broad and exciting introduction to the field ofcomputer science and the impact that computation has today on everyaspect of life. It focuses on exploring computing as a creative activityand investigates the key foundations of computing: abstraction, data,algorithms, and programming. It looks into how connectivity and theInternet have revolutionized computing and demonstrates the globalimpact that computing has achieved, and it reveals how a new student incomputer science might become part of the computing future.Prerequisite(s): MATH 1215 or higher.C S 117. Introduction to Computer Animation3 Credits (3)Introductory course for learning to program with computer animation aswell as learning basic concepts in computer science. Students createinteractive animation projects such as computer games and learn to usesoftware packages for creating animations in small virtual worlds using3D models. Recommended for students considering a minor/major incomputer science or simply interested in beginning computer animationor programming.C S 151. C Programming3 Credits (2 2P)Introduction to object-oriented programming in the C language. Thefocus will be on preparing students to use C in their own areas. Noprior programming experience is required. Taught with C S 451.Prerequisite: MATH 1215 or higher.Learning Outcomes1. Use various data types and the corresponding operations. Write C programs that contain expressions, program control, functions,arrays, and input/output Explain basic object-oriented programmingconcepts. Demonstrate proficiency in using classes, inheritance,pointers, streams, and recursionC S 152. Java Programming3 Credits (2 2P)Programming in the Java language. May be repeated up to 3 credits.Prerequisite(s): MATH 1215 or higher.1C S 153. Python Programming I3 Credits (3)This course is an introduction to programming in the Python language,covering fundamental scripts, data types and variables, functions, andsimple object creation and usage. The focus will be on preparing studentsto use Python in their own areas. No prior programming experience isrequired. Taught with C S 453.Prerequisite: MATH 1215 or higher.Learning Outcomes1. Develop an algorithm to solve a problem Demonstrate the ability touse Python data types: int, float, strings, and lists; and the built-infunctions associated with those data types Edit and debug programsusing the Spyder IDE for Python Implement algorithms using thePython features of assignment, input, output, branches, loops, andfunctions Explain the fundamental concepts of object-orientedprogramming with Python Design and implement Python classesbased on given attributes and behaviors Work with existing Pythonmodules such as math, random, and os Write Python programs thatinput data from files and store results in filesC S 154. Python Programming II3 Credits (3)This course covers advanced Python programming, including classes,objects, and inheritance, embedded programming in domain applications,database interaction, and advanced data and text processing. The focuswill be on preparing students to use Python in their own areas.Prerequisite(s): C S 153 or C S 453.C S 157. Topics in Software Programming and Applications3 Credits (2 2P)Current topics in computer programming and software applications.Topic announced in the Schedule of Classes. May be repeated if subtitleis different.C S 158. R Programming I3 Credits (3)This course is an introduction to data processing in the R language,covering fundamental script configuration, data types and datacollections, R control structures, and basic creation of graphs and datavisualizations. This course will not focus on the statistical capabilities ofR, though some basic statistical computations will be used.Prerequisite(s): MATH 1220G.C S 171G. Introduction to Computer Science4 Credits (3 2P)Computers are now used widely in all area of modern life. This courseprovides understanding of the theoretical and practical foundationsfor how computers work, and provides practical application andprogramming experience in using computers to solve problems efficientlyand effectively. The course covers broad aspects of the hardware,software, and mathematical basis of computers. Weekly labs stressusing computers to investigate and report on data-intensive scientificproblems. Practical experience in major software applications includesan introduction to programming, word processing, spreadsheets,databases, presentations, and Internet applications.Prerequisite(s): MATH 1130G or MATH 1215 or higher.
2Computer ScienceC S 172. Computer Science I4 Credits (3 2P)Computational problem solving; problem analysis; implementation ofalgorithms using Java. Object-oriented concepts, arrays, searching,sorting, and recursion. Taught with C S 460Prerequisite: (A C or better in either MATH 1250G or MATH 1430G) OR (AC or better in MATH 1220G and a 1 or better in the CS Placement Test).Learning Outcomes1. Develop algorithms to solve problems Implement algorithms usingthe fundamental programming features of sequence, selection,iteration, and recursion2. Apply an understanding of primitive and object data types3. Design and implement classes based on given attributes andbehaviors4. Explain the fundamental concepts of object-oriented programming,C S 209. Special Topics.1-3 CreditsMay be repeated for a maximum of 12 credits.C S 271. Object Oriented Programming4 Credits (3 2P)Introduction to problem analysis and problem solving in the objectoriented paradigm. Practical introduction to implementing solutions inthe C language. Pointers and dynamic memory allocation. Hands-onexperience with useful development tools. Taught with C S 462.Prerequisite: At least a C- in C S 172 or E E 112.Learning Outcomes1. Develop an algorithm to solve a problem. Implement algorithms usingthe C and C languages including imperative and object-orientedlanguage features. Beyond what was learned in C S 172, E E 112, or EE 161 demonstrate a noticeable increase in understanding of problemanalysis and program design. Demonstrate proficiency in usingcontrol structures including if statements (single selection), switch(multiple selection), and loops (repetition). Demonstrate proficiencyin using arrays and functions Create UML class and relationshipdiagrams. Design a class to model a real-world person, place, thing,or event. Use editing and debugging software to create, debug, andtest C and C programs. Understand the basic terminology usedin object-oriented programming. 1 Create a make file to build anexecutable from a set of C or C source files.C S 272. Introduction to Data Structures4 Credits (3 2P)Design, implementation, use of fundamental abstract data types andtheir algorithms: lists, stacks, queues, deques, trees; imperative anddeclarative programming. Internal sorting; time and space efficiency ofalgorithms. Taught with C S 463.Prerequisite: At least a C- in C S 172, or placement.Learning Outcomes1. Be able to implement and use lists Be able to implement and usestacks Be able to implement and use queues Be able to implementand use trees Be able to perform the run time analysis of basicalgorithms using Big O notation Be able to implement, use, andanalyze searching algorithms Be able to solve a problem recursivelyTake a problem statement from a user and convert it into a Javaprogram that fulfills the user’s needs Create object oriented Javaclasses that effectively separate and hide implementation detailsfrom client applicationsC S 273. Machine Programming and Organization4 Credits (3 2P)Computer structure, instruction execution, addressing techniques;programming in machine and assembly languages. Taught with C S 464.Prerequisite: At least a C- in C S 172 or E E 112.Learning Outcomes1. Describe the architecture of a microcontroller, the interconnectionsbetween the components, and the basic units inside the CPU Usesigned and unsigned numbers, the associated branching instructions,and the corresponding flags in the status register Explain immediate,direct, indirect addressing modes, their opcode and operands, andtheir utilities Map high-level programming language features toassembly instructions, including loops, conditionals, procedure calls,value and reference parameter passing, return values, and recursionInterface with I/O devices including LED and sensors via digitalinput and output, and analog-to-digital conversion Program timers/counters and interrupts to control real-time applications Design anassembly programC S 278. Discrete Mathematics for Computer Science4 Credits (3 2P)Discrete mathematics required for Computer Science, includingthe basics of logic, number theory, methods of proof, sequences,mathematical induction, set theory, counting, and functions. Taught withC S 465.Prerequisite: At least C- in C S 172.Learning Outcomes1. Use logic to specify precise meaning of statements, demonstratethe equivalence of statements, and test the validity of argumentsConstruct and recognize valid proofs using different techniquesincluding the principle of mathematical induction Use summations,formulas for the sum of arithmetic and geometric sequencesExplain and apply the concepts of sets and functions Apply countingprinciples to determine the number of various combinatorialconfigurationsC S 343. Algorithm Design & Implementation3 Credits (3)Introduction to efficient data structure and algorithm design. Basic graphalgorithms. Balanced search trees. Classic algorithm design paradigms:divide-and-conquer, greedy scheme, and dynamic programming. Taughtwith C S 493.Prerequisite: At least a C- in C S 272, or consent of instructor.Learning Outcomes1. Be able to use and implement sorting algorithms Be able to designand implement graph algorithms Be able to design and implementalgorithms using the divide-and-conquer technique Be able to designand implement algorithms using the greedy technique Be able todesign and implement algorithms using the dynamic programmingtechnique Be able to use and implement balanced search trees Beable to use and implement hashing techniques Be able to perform therun time analysis of basic algorithms using Big O notation
Computer ScienceC S 370. Compilers and Automata Theory4 Credits (3 2P)Methods, principles, and tools for programming language processordesign; basics of formal language theory (finite automata, regularexpressions, context-free grammars); development of compilercomponents. Taught with C S 466.Prerequisite: At least a C- in C S 271, C S 272, and C S 273.Learning Outcomes1. Understand the language theory concepts of regular languages,context free languages, regular expressions, context free grammars,and formal language hierarchy Use Thompson's construction toconvert from regular expression to NFA, and subset constructionto convert from NFA to DFA Apply recursive descent parsing inprogramming a parser of a small grammar Understand the ideas in LLand LR parsing of context-free language classes Understand and usetable-driven top-down (LL(1)) and bottom up (SLR) parsing to parse asentenceC S 371. Software Development4 Credits (3 2P)Software specification, design, testing, maintenance, documentation;informal proof methods; team implementation of a large project. Taughtwith C S 468.Prerequisite: At least a C- in C S 271 and C S 272.Learning Outcomes1. Understand and explain the activites and structure of different stylesof software development processes, including waterfall, (spiral,)iterative, and agile methodologies Apply requirements knowledgeand techniques to create functional and non-functional requirementsfor a software system Apply high and low level design ideas tocreate an object-oriented design of a software system Use gooddesign and programming ideas to implement individual and teamsoftware systems in compiled OOP languages Apply white and blackbox testing techniques and tools to individual and team softwaredevelopment Use UML class diagrams (and sequence diagrams) tocapture aspects of system design and/or requirements (domain)Use practical software development tools, including version controlsystems, automated build tools, and testing toolsC S 372. Data Structures and Algorithms4 Credits (3 2P)Introduction to efficient data structure and algorithm design. Ordernotation and asymptotic run-time of algorithms. Recurrence relations andsolutions. Abstract data type dynamic set and red-black trees. Classicalgorithm design paradigms: divide-and-conquer, dynamic programming,greedy algorithms. Taught with C S 469.Prerequisite: At least a C- in CS 272 and C S 278.Learning Outcomes1. Analyze the growth of functions via asymptotic notation Evaluatethe asymptotic running time of a given algorithm Solve recurrencerelations of the kinds encountered in algorithm analysis Designalgorithms using the divide-and-conquer technique Design algorithmsusing the greedy technique Design algorithms using the dynamicprogramming technique Use and analyze balanced binary searchtrees Analyze the design, correctness, and time complexity of basicgraph algorithms3C S 380. Introduction to Cryptography3 Credits (3)The course covers basic cryptographic primitives, such as symmetric,public-key ciphers, digital signature schemes, and hash functions, andtheir mathematical underpinnings. Course helps students understandbasic notions of security in a cryptographic sense: chosen plaintext andchosen ciphertext attacks, games, and reductions. Course also coverscomputational number theory relevant to cryptography. Consent ofInstructor required. Taught with: C S 525.Prerequisite: C S 278 (or equivalent) with a C or better.Learning Outcomes1. Describe basic cryptographic primitives, including symmetric ciphers,asymmetric ciphers, digital signatures, message authenticationcodes, and hash functions. Understand the mathematical,fundamental underpinnings of cryptography, and how to reason aboutthe security of crypto primitives: indistinguishability (IND) propertiesof ciphertexts, CPA/CCA games, and reductions to fundamental mathassumptions; Be able to discuss number theory/algebra underpinningthe design of cryptographic primitives, in some depth.C S 382. Modern Web Technologies3 Credits (3)In this course, we will take a full-stack approach to modern webapplication design. We will start with the fundamentals including HTML5,CSS3, Javascript, JSON, and the underlying networking conceptsand protocols driving the modern web. We will then move on to moreadvanced topics including javascript backend development with Node.js,NoSQL database design with MongoDB, cloud computing, and responsive web design. Finally, we cover advanced topics including thedesign and im- plementation of browser extensions and real-time webtechnologies like WebRTC and WebSockets. Consent of Instructorrequired. Taught with: C S 532.Learning Outcomes1. Understand the fundamental technologies and operation of the web.Design and develop responsive interactive web sites. Deploy webapplications on Cloud Computing Platforms. Leverage modern toolsand packages to develop full stack web applications. Be fluent in theapplication of emerging web technologies like browser extensions,WebSockets, and WebRTC. Use existing materials and references onthe web to learn new skills.C S 409. Independent Study1-6 Credits (1-6)Faculty supervised investigation, to culminate in a written report. May berepeated up to 6 credits.Prerequisite(s): Written agreement with faculty supervisor.C S 419. Computing Ethics and Social Implications of Computing1 Credit (1)An overview of ethics for computing majors includes: history ofcomputing, intellectual property, privacy, ethical frameworks, professionalethical responsibilities, and risks of computer-based systems.Prerequisite: At least a C- in C S 371.Learning Outcomes1. Understand the fundamental technologies and operation of the web.Design and develop responsive interactive web sites. Deploy webapplications on Cloud Computing Platforms. Leverage modern toolsand packages to develop full stack web applications. Be fluent in theapplication of emerging web technologies like browser extensions,WebSockets, and WebRTC. Use existing materials and references onthe web to learn new skills.
4Computer ScienceC S 448. Senior Project4 Credits (4)Capstone course in which C S majors work in teams and apply computerscience skills to complete a large project. Restricted to: C S majors.Prerequisite: At least a C- in C S 370 and C S 371.Learning Outcomes1. Apply design and development principles in the constructionof software systems of varying complexity Apply mathematicalfoundations, algorithmic principles, and computer science theoryin the modeling and design of computer-based systems in a waythat demonstrates comprehension of the tradeoffs involved indesign choices Design, implement, and evaluate a computer-basedsystem, process, component, or program to meet desired needsUse current techniques, skills, and tools necessary for computingpractice Analyze a problem, and identify and define the computingrequirements appropriate to its solution Function effectively as teamsto accomplish a common goal Communicate effectively with a rangeof audiencesC S 449. Senior Thesis4 Credits (4)Capstone course in which C S majors apply computer science skillsto complete a research project, culminating in a written thesis report.Restricted to: C S majors.Prerequisite: At least a C- in C S 370 and C S 371.Learning Outcomes1. Apply design and development principles in the constructionof software systems of varying complexity Apply mathematicalfoundations, algorithmic principles, and computer science theoryin the modeling and design of computer-based systems in a waythat demonstrates comprehension of the tradeoffs involved indesign choices Design, implement, and evaluate a computer-basedsystem, process, component, or program to meet desired needs Usecurrent techniques, skills, and tools necessary for computing practiceAnalyze a problem, identify, and define the computing requirementsappropriate to its solution Communicate effectively with a range ofaudiences via presentations and technical reportsC S 451. C Programming3 Credits (3)Programming in the C language. Taught with C S 151. Required moreadvanced graduate work than C S 151. Recommended for nonmajorsonly. Not for CS undergraduate students.Learning Outcomes1. Use various data types and the corresponding operations. Write C programs that contain expressions, program control, functions,arrays, and input/output. Explain basic object-oriented programmingconcepts. Demonstrate proficiency in using classes, inheritance,pointers, streams, and recursion.C S 452. Java Programming3 Credits (2 2P)Programming in the Java language. More advanced than C S 152.Recommended for nonmajors only. Not for CS undergraduate standing.May be repeated up to 3 credits.C S 453. Python Programming I3 Credits (3)This course is an introduction to programming in the Python language,covering fundamental scripts, data types and variables, functions, andsimple object creation and usage. The focus will be on preparing studentsto use Python in their own areas. No prior programming experience isrequired. Taught with C S 153. More advanced than C S 153.Learning Outcomes1. Develop an algorithm to solve a problem Demonstrate the ability touse Python data types: int, float, strings, and lists; and the built-infunctions associated with those data types Edit and debug programsusing the Spyder IDE for Python Implement algorithms using thePython features of assignment, input, output, branches, loops, andfunctions Explain the fundamental concepts of object-orientedprogramming with Python Design and implement Python classesbased on given attributes and behaviors Work with existing Pythonmodules such as math, random, and os Write Python programs thatinput data from files and store results in filesC S 454. Python Programming II3 Credits (3)This course covers advanced Python programming, including classes,objects, and inheritance, embedded programming in domain applications,database interaction, and advanced data and text processing. The focuswill be on preparing students to use Python in their own areas. Forgraduate students only. Has more advanced work than C S 154, and doesnot count towards CS major requirements. Not for CS undergraduatestudents. May be repeated up to 3 credits. Restricted to: exclude C Smajors.Prerequisite(s): C S 153 or C S 453.C S 457. Topics in Software Programming and Applications3 Credits (2 2P)Current topics in computer programming and software applications.Topic announced in the Schedule of Classes. More advanced thanC S 157. recommended for non-majors only. May be repeated if subtitle isdifferent.Prerequisite(s): Graduate standing.C S 458. R Programming I3 Credits (3)This course is an introduction to data processing in the R language,covering fundamental script configuration, data types and datacollections, R control structures, and basic creation of graphs and datavisualizations. This course will not focus on the statistical capabilities ofR, though some basic statistical computations will be used. For graduatestudents only. Has more advanced work than C S 158. Does not counttowards CS major requirements. May be repeated up to 3 credits.Prerequisite(s): Good understanding of college algebra or higher.C S 460. Computer Science I Transition3 Credits (3)Computational problem solving; problem analysis; implementationof algorithms. Recursive structures and algorithms. For C S graduatestudents only; cannot be used to meet a C S student's program of study.Taught with C S 172.Learning Outcomes1. Develop algorithms to solve problems Implement algorithms usingthe fundamental programming features of sequence, selection,iteration, and recursion Apply an understanding of primitive andobject data types Design and implement classes based on givenattributes and behaviors Explain the fundamental concepts of objectoriented programming
Computer ScienceC S 462. Object Oriented Programming Transition3 Credits (3)Introduction to problem analysis and problem solving in the objectoriented paradigm. Practical introduction to implementing solutions inthe C language. Hands-on experience with useful development tools.Cannot be used in a C S student's program of study. Consent of Instructorrequired. Taught with C S 271.Prerequisite: At least a C- in C S 172 or C S 460 or consent of instructor.Learning Outcomes1. Develop an algorithm to solve a problem. Implement algorithmsusing the C and C languages including imperative and objectoriented language features. Demonstrate a noticeable increase inunderstanding of problem analysis and program design beyondwhat was learned in C S 172, E E 112, or E E 161 Demonstrateproficiency in using control structures including if statements(single selection), switch (multiple selection), and loops (repetition).Demonstrate proficiency in using arrays and functions. Create UMLclass and relationship diagrams. Design a class to model a real-worldperson, place, thing, or event. Use editing and debugging software tocreate, debug, and test C and C programs. Understand the basicterminology used in object-oriented programming. 1Create a make fileto build an executable from a set of C or C source files.C S 463. Introduction to Data Structures Transition3 Credits (3)Design, implementation, use of fundamental abstract data types andtheir algorithms: lists, stacks, queues, deques, trees; imperative anddeclarative programming. Internal sorting; time and space efficiency ofalgorithms. Cannot be used in a C S student's program of study. Consentof Instructor required. Taught with C S 272.Prerequisite: At least a C- in C S 172 or C S 460 or consent of instructor.Learning Outcomes1. Be able to implement and use lists Be able to implement and usestacks Be able to implement and use queues Be able to implementand use trees Be able to perform the run time analysis of basicalgorithms using Big O notation Be able to implement, use, andanalyze searching algorithms Be able to solve a problem recursivelyTake a problem statement from a user and convert it into a Javaprogram that fulfills the user’s needs Create object oriented Javaclasses that effectively separate and hide implementation detailsfrom client applications5C S 464. Machine Programming and Organization Transition3 Credits (3)Computer structure, instruction execution, addressing techniques;programming in machine and assembly languages. Cannot be used in a CS student's program of study. Consent of Instructor required. Taught withC S 273.Prerequisite: At least a C- in C S 172 or C S 460 or consent of instructor.Learning Outcomes1. Describe the architecture of a microcontroller, the interconnectionsbetween the components, and the basic units inside the CPU Usesigned and unsigned numbers, the associated branching instructions,and the corresponding flags in the status register Explain immediate,direct, indirect addressing modes, their opcode and operands, andtheir utilities Map high-level programming language features toassembly instructions, including loops, conditionals, procedure calls,value and reference parameter passing, return values, and recursionInterface with I/O devices including LED and sensors via digitalinput and output, and analog-to-digital conversion Program timers/counters and interrupts to control real-time applications Design anassembly programC S 465. Discrete Math for Computer Science Transition3 Credits (3)Logical connectives, sets, functions, relations, graphics, trees, proofs,induction, and application to computer science. For C S graduatestudents only. Cannot be used in a C S student's program of study.Consent of Instructor required. Taught with C S 278.Prerequisite: At least a C- in C S 172 or C S 460 or consent of instructor.Learning Outcomes1. Use logic to specify precise meaning of statements, demonstratethe equivalence of statements, and test the validity of argumentsConstruct and recognize valid proofs using different techniquesincluding the principle of mathematical induction Use summations,formulas for the sum of arithmetic and geometric sequencesExplain and apply the concepts of sets and functions Apply countingprinciples to determine the number of various combinatorialconfigurationsC S 466. Compilers and Automata Transition3 Credits (3)Methods, principles, and tools for programming language processordesign; basics of formal language theory (finite automata, regularexpressions, context-free grammars); development of compilercomponents. For C S graduate students only; cannot be used in astudents program of study. Taught with C S 370.Prerequisite: At least a C in (C S 271 or C S 462), in (C S 272 or C S 463),in (C S 273 or C S 464), or consent of instructor.Learning Outcomes1. Understand the language theory concepts of regular languages,context free languages, regular expressions, context free grammars,and formal language hierarchy Use Thompson's construction toconvert from regular expression to NFA, and subset constructionto convert from NFA to DFA Apply recursive descent parsing inprogramming a parser of a small grammar Understand the ideas in LLand LR parsing of context-free language classes Understand and usetable-driven top-down (LL(1)) and bottom up (SLR) parsing to parse asentence
6Computer ScienceC S 468. Software Development Transition3 Credits (3)Software specification, design, testing, maintenance, documentation;informal proof methods; team implementation of a large project. For CS graduate students only. Cannot be used in a C S student's program ofstudy. Consent of Instructor required. Taught with C S 371.Prerequisite: At least a C- in C S 271 or C S 462, in C S 272 or C S 463, orconsent of instructor.Learning Outcomes1. Understand and explain the activites and structure of different stylesof software development processes, including waterfall, (spiral,)iterative, and agile methodologies Apply requirements knowledgeand techniques to create functional and non-functional requirementsfor a software system Apply high and low level design ideas tocreate an object-oriented design of a software system Use gooddesign and programming ideas to implement individual and teamsoftware systems in compiled OOP languages Apply white and blackbox testing techniques and tools to individual and team softwaredevelopment Use UML class diagrams (and sequence diagrams) tocapture aspects of system design and/or requirements (domain)Use practical software development tools, including version controlsystems, automated build tools, and testing toolsC S 469. Data Structure and Algorithms Transition3 Credits (3)Introduction to efficient data structure and algorithm design. Ordernotation and asymptotic run-time of algorithms. Recurrence relations andsolutions. Abstract data type dynamic set and red-black trees. Classicalgorithm design paradigms: divide-and-conquer, dynamic programming,greedy algorithms. For C S graduate students only. Consent of Instructorrequired. Taught with C S 372.Prerequisite: At least a C- in C S 272 or C S 463, in C S 278 or C S 465, orconsent of instructor.Learning Outcomes1. Analyze the growth of functions via asymptotic notation Evaluatethe asymptotic running time of a given algorithm Solve recurrencerelations of the kinds encountered in algorithm analysis Designalgorithms using the divide-and-conquer technique Design algorithmsusing the greedy technique Design algorithms using the dynamicprogramming technique Use and analyze balanced binary searchtrees Analyze the design, correctness, and time complexity of basicgraph algorithmsC S 471. Programming Language Structure I3 Credits (3)Syntax, semantics, implementation, and application of programminglanguages; abstract data types; concurrency. Not for C S graduatestudents.Prerequisite: At least a C- in C S 370 and C S 371.Learning Outcomes1. Improve the background for choosing appropriate programmingla
algorithms, and programming. It looks into how connectivity and the . Introductory course for learning to program with computer animation as well as learning basic concepts in computer science. Students create . Computer structure, instruction execution, addressing techniques; programmin
Board Endorsed Courses There are two types of Board Endorsed Courses - Content Endorsed Courses and School Designed Courses. 1. Content Endorsed Courses (CEC) have syllabuses endorsed by the Board of Studies to cater for areas of special interest not covered in the Board Developed Courses. 2. Schools may also design courses to meet student needs.
Computer Engineering - three majors More or less same lower division requirements (numbered 1-99) Math, Computer Engineering, Computer Science and Physics Computer Engineering major (minimum of 14 upper division courses, numbered 100-199) 8 required courses 4 -5 elective courses, depending on concentration 2-3 senior design or thesis courses
in computer science courses, and there were roughly 22 students enrolled for every credentialed computer science teacher in the state. Figure 2. Arkansas High School Enrollment in Computer Science Courses, 2014-2020. Student enrollment in computer science degree programs at postsecondary institutions in Arkansas has also been rising.
Board Developed Courses (minimum 6 units – usually 3 courses) 2. Vocational Education and Training (VET) courses. Students may choose from Category B NESA (New South Wales Education Standards Authority) courses - that can be studied at Erskine Park High School, or TAFE. 3. Board Endorsed Courses. These are courses that the NESA has approved
In year 1 and 2 the students learn the basic, foundation and compulsory courses according to the weightage given by the HEC. These courses include i) Compulsory courses, ii) Core Courses from Zoology, iii) Supporting Minor Courses from Botany and Chemistry and iv) Elective Courses e.g., St
c. Computer Aided Manufacturing Technician - 4 courses for a certificate, courses can be used for Computer Integrated Manufacturing degree. d. Precision Machining Technology - 4 courses for a certificate, courses can be used for Precision Machining associate's degree e. Industrial Controls: Programmable Logic Controller - 3 courses for a
This handbook supplement applies to students entering the fourth year of their degree in Computer Science, Mathematics & Computer Science or Computer Science . Undergraduate Course Handbook 1.2 Mathematics & Computer Science The Department of Computer Science offers the following joint degrees with the Department of Mathematics: BA .
A variety of courses in a computer science curriculum contain a hardware component; courses such as digital design, computer organization and architecture, real-time (embedded) systems, and even breadth based introductory courses [7]. These courses will usually use either breadboards or h
