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CSC CoursesSCI199Y1
Undergraduate seminar that focuses on specific ideas, questions, phenomena or controversies, taught by a regular Faculty member deeply engaged in the discipline. Open only to newly admitted first year students. It may serve as a distribution requirement course; see page 44. NOTE CSC104H1
Computer parts and their interconnection. Software: operating systems, files, interfaces. Hardware: storage media, memory, data representation, I/O devices. History of computing. Problem solving with computers: algorithms and basic programming concepts. Science and computer science; graphics, artificial intelligence. Common computer applications: databases, simulations. Implications for society: computers and work, office automation, computer security. (Students work with various applications and software, but the aim is to discuss general concepts of computer applications, not to serve as a tutorial for specific packages.) CSC107H1
Through independent study, students learn the material at their own pace. Structure of computers; the computing environment; programming in an object-oriented language such as Java. Program structure in an object-oriented language: classes, objects, methods, fields. Internal structure of methods: elementary data types, statements, control flow. Arrays; searching, sorting and complexity. CSC108H1
Structure of computers; the computing environment. Programming in an object-oriented language such as Java. Program structure in an object-oriented language: classes, objects, methods, fields. Internal structure of methods: elementary data types, statements, control flow. Arrays; searching, sorting and complexity. Practical (P) sections consist of supervised work in the computing laboratory. These sections are offered when facilities are available, and attendance is required. CSC148H1
Abstract data types and data structures for implementing them. Linked data structures. Encapsulation and information-hiding. Object-oriented programming in a language such as Java. Specifications. Analyzing the correctness and efficiency of programs using mathematical reasoning. Recursion. Recurrence relations for analyzing the efficiency of recursive code. This course assumes programming experience in an object-oriented language such as C++ or Java, as provided by CSC108H1. Students who already have this background may consult the Computer Science Undergraduate Office for advice about skipping CSC108H1. Practical (P) sections consist of supervised work in the computing laboratory. These sections are offered when facilities are available, and attendance is required. CSC150H1
An accelerated course covering all the material of CSC148H1 and also object-oriented topics (classes, objects, methods and fields, and program design). Suitable for students with a solid programming background in Turing, C, Pascal or a similar language, who are willing to accept a heavier workload than in CSC108H1 and CSC148H1 CSC165H1
Introduction to abstraction and rigour. Understanding, using and developing precise expressions of mathematical ideas, including definitions and theorems. Informal introduction to logical notation and reasoning. CSC209H1
Software development techniques, typically in the UNIX environment. Particular emphasis on what happens in the system when programs run. Core topics: software utilities (e.g. pipes, filters) shell programming, system calls, signals, file processing, introduction to concurrency (e.g. synchronization, mutual exclusion, race conditions, producer-consumer problem), processes. Additional topics may include: scripting languages, network programming (e.g. sockets). CSC228H1
An introduction to techniques for storing, accessing and managing long-term data in computer systems. Hardware and software aspects of data processing: processors, storage devices, communications, file I/O control. Techniques for organizing and managing files: serial files, direct files, indexed files, multikey files, integrated files, file systems. Introduction to data base management systems with emphasis on relational data base systems. CSC230H1
Logic and its use as a declarative language in computer science. Syntax and semantics of propositional and predicate calculus. Proving entailment and non-entailment rigorously. Formal derivations. Applications, including information systems, program verification, artificial intelligence, software engineering. Computational tools, including Prolog. Other logics. CSC236H1
The rigorous application of logic and proof techniques to Computer Science. Mathematical induction; correctness proofs for iterative and recursive algorithms; recurrence equations and their solutions; properties of languages. CSC238H1
A rigorous treatment of certain aspects of discrete mathematics, with applications to Computer Science. Topics include mathematical induction, program correctness, recurrences, divide-and-conquer algorithms, finite state machines, and an introduction to the propositional and predicate calculus. CSC258H1
Computer structures, machine languages, instruction execution, addressing techniques, and digital representation of data. Computer system organization, memory storage devices, and microprogramming. Block diagram circuit realizations of memory, control and arithmetic functions. There are a number of laboratory periods in which students conduct experiments with digital logic circuits. CSC260H1
Problems in transforming continuous mathematical models to discrete computational models. Inadequacy of naive computer solutions, and techniques to remedy inadequacies. Symbolic computation, plotting, 3-D graphics, and conventional programming languages. Intended for students from computer science, sciences and mathematics: for computer scientists, introduction to design and implementation of robust algorithms; for scientists, techniques in transforming scientific problems into computational solutions; for mathematicians, insight into differences between mathematical models and computational solutions. CSC270H1
Standard programming methods, with an introduction to C and C++. Use of classes to represent abstract data types. Graph representation and graph algorithms. Simulation: data structures and program organization for event-driven models. Representation of floating-point numbers; introduction to numerical methods. Optimization using dynamic programming. Programming assignments stress both the proper use of abstract data types (lists, stacks, trees, heaps) and approaches to writing larger, more complex programs. CSC300H1
Privacy and Freedom of Information; recent Canadian legislation and reports. Computers and work; employment levels, quality of working life. Electronic fund transfer systems; transborder data flows. Computers and bureaucratization. Computers in the home; public awareness about computers. Robotics. Professionalism and the ethics of computers. The course is designed not only for science students, but also those in social sciences or humanities. CSC309H1
An introduction to software development on the web. Concepts underlying the development of programs that operate on the web; survey of technological alternatives; greater depth on some technologies. Operational concepts of the internet and the web, static client content, dynamic client content, dynamically served content, n-tiered architectures, web development processes, and security on the web. Assignments involve increasingly more complex web-based programs. Guest lecturers from leading e-commerce firms will describe the architecture and operation of their web sites. 26L, 13T CSC310H1
Measuring information. The source coding theorem. Data compression using ad hoc methods and dictionary-based methods. Probabilistic source models, and their use via Huffman and arithmetic coding. Noisy channels and the channel coding theorem. Error correcting codes, and their decoding by algebraic and probabilistic methods. CSC318H1
User-centred design of interactive systems; methodologies, principles, and metaphors; task analysis. Interdisciplinary design; the role of graphic design, industrial design, and the behavioural sciences. Interactive hardware and software; concepts from computer graphics. Typography, layout, colour, sound, video, gesture, and usability enhancements. Classes of interactive graphical media; CSC320H1
A unified introduction to image synthesis and image analysis aimed at students with an interest in computer graphics, computer vision or the visual arts. Focus on three major topics: (1) visual computing principles - computational and mathematical methods for creating, capturing, analyzing and manipulating digital photographs (raster algorithms, image acquisition, basic image processing, image warping, anti-aliasing); (2) digital special effects - applying these principles to create special effects found in movies and commercials; (3) visual programming - using C/C++ and OpenGL to create graphical user interfaces for synthesizing and manipulating photographs. CSC321H1
Supervised neural networks: the perceptron learning procedure, the backpropagation learning procedure and its applications. Elaborations of backpropagation: activation and error functions, improving speed and generalization, Bayesian approaches. Associative memories and optimization: Gibbs sampling, mean field search. Representation in neural networks: distributed representations, effects of damage, hierarchical representations. Unsupervised neural networks: competitive learning, Boltzmann machines, sigmoid belief nets. CSC324H1
Major topics in the development of modern programming languages. Syntax specification, type systems, type interface, exception handling, information hiding, structural recursion, run-time storage management, and programming paradigms. Two non-procedural programming paradigms: functional programming (illustrated by languages such as Lisp, Scheme, ML or Haskell) and logic programming (illustrated by languages such as Prolog, XSB or Coral). CSC336H1
The study of computational methods for solving problems in linear algebra, non-linear equations, approximation, integration, and ordinary differential equations. The aim is to give students a basic understanding of both floating-point arithmetic and the methods used to solve numerical problems as well as a familiarity with the types of subroutines found in typical software packages. CSC340H1
Theory, tools and techniques of information systems analysis and design. Topics include: theory of systems and organizations; structured analysis and design; user interface design. CSC343H1
Concepts, approaches, and techniques in data base management systems (DBMS): relational data bases, querying and updating a data base, query language SQL, data base constraints and data base design, elements of data base technology. CSC350H1
Floating-point arithmetic. The efficiency and stability of solution techniques for systems of linear equations and least squares problems, including LU- and QR-based methods. Eigenvalue and eigenvector calculations. Algorithms for systems of non-linear equations and optimization problems, including linear programming. CSC351H1
Analysis of methods for approximation, integration and the solution of ordinary differential equations. Emphasis on the convergence and stability properties of the algorithms, rather than on their implementation. CSC354H1
Simulation and mathematical analysis of models of queuing systems. Concentration on dynamic, stochastic, discrete-event systems. Simulation topics: selecting input probability distributions, generating random numbers and random variates, output data analysis for one or more system configurations, variance reduction techniques. Analysis topics: queuing characteristics, transient and steady-state behaviour, performance measures, the M/M/1 queue in detail, some non-Markovian queues. CSC364H1
General techniques for efficient algorithm design: greedy algorithms, dynamic programming; other topics may include network flow, linear programming, randomized algorithms. Introduction to complexity theory: models of computation, the classes P and NP, polynomial time reducibility and NP-completeness, provably hard problems. Introduction to the theory of computability: Church’s thesis, computable and noncomputable functions, reductions, the analogies between complexity and computability theory. CSC372H1
Development of reliable efficient software for controlling and monitoring an environment. Concurrent programming techniques, such as interrupt handling, buffer management, polling and time outs. Projects use microprocessors to control equipment (such as a robot arm) and to read sensors. Design, implementation and testing of software using high level software, such as Turing or C. CSC378H1
Abstract data types such as priority queues and dictionaries. Advanced data structures for main memory resident information, such as binomial heaps, leftist trees, self-adjusting lists and balanced search trees. Algorithm analysis: worst case, average case, and amortized complexity. Introduction to lower bounds. Emphasis is given to problem solving and a theoretical treatment of the data structures. CSC384H1
A broad introduction to the sub-disciplines of AI. Core topics: search methods, game playing and rule-based systems. Overview of: natural language understanding, knowledge representation, reasoning, planning, vision, robotics, learning and neural networks. Assignments provide practical experience, both theory and programming, of the core topics. LISP or Prolog programming is required for at least one assignment. CSC401H1
Introduction to techniques involving natural language and speech in applications such as information retrieval, extraction, and filtering; intelligent Web searching; spelling and grammar checking; speech recognition and synthesis; and multi-lingual systems including machine translation. N-grams, POS-tagging, semantic distance metrics, indexing, on-line lexicons and thesauri, markup languages, collections of on-line documents, corpus analysis. PERL and other software. CSC407H1
An introduction to the development of system-level architectures and class-level object-oriented designs for software systems. Special emphasis on the study of architecture and design patterns: the core of solutions to commonly occurring design problems. Representations of design/architecture (with emphasis on the use of UML as a class-level design notation), architectural assessment, product lines, architecture extraction, and re-factoring. There is no major project, but there is a series of smaller design and architecture exercises requiring some programming. A knowledge of UML as used for requirements analysis and a working knowledge of both the C++ and Java languages are assumed. CSC408H1
The structure and unique characteristics of large software systems. The software process and software project management including project planning, risk management, staffing and organizational issues. Review of requirements analysis and specification. Software development techniques, version control, configuration management, system construction tools. Software system testing and quality assurance. Software maintenance and product delivery strategies. A course project is used to illustrate software engineering techniques. CSC411H1
An introduction to methods for automated learning of relationships on the basis of empirical data. Classification and regression using nearest neighbour methods, decision trees, linear models, and neural networks. Clustering algorithms. Problems of overfitting and of assessing accuracy. Problems with handling large databases. CSC412H1
Representing uncertain knowledge using probability and other formalisms. Qualitative and quantitative specification of probability distributions using graphical models. Algorithms for inference with graphical models. Statistical approaches and algorithms for learning models from experience. Application of these models in other areas of artificial intelligence and to problems such as medical diagnosis. CSC418H1
Identification and characterization of the objects manipulated in computer graphics, the operations possible on these objects, efficient algorithms to perform these operations, and interfaces to transform one type of object to another. Display devices, display data structures and procedures, graphical input, object modelling, transformations, illumination models, primary and secondary light effects; graphics packages and systems. Students, individually or in teams, implement graphical algorithms or entire graphics systems. CSC420H1
Introduction to fundamental concepts in image understanding, the subdiscipline of artificial intelligence dealing with the automation of visual tasks by computer. Exploration of a number of real-world image interpretation problems, as motivation for key low- and intermediate-level vision algorithms. A course project will include the construction of a number of practical vision systems. Offered in winter 2004. CSC428H1
Understanding human behaviour as it applies to user interfaces: work activity analysis, observational techniques, questionnaire administration and unobtrusive measures. Operating parameters of the human cognitive system, task analysis and cognitive modelling techniques and their application to designing interfaces. Interface representations and prototyping tools. Cognitive walkthroughs, usability studies and verbal protocol analysis. Case studies of specific user interfaces. CSC438H1
Computable functions, Church’s thesis, unsolvable problems, recursively enumerable sets. Predicate calculus, including the completeness, compactness, and Lowenheim-Skolem theorems. Formal theories and the Gödel Incompleteness Theorem. CSC443H1
Technology of a database management system: storage and memory management, query and transaction processing, parallel and distributed architectures. Modern application of database systems: data mining, data warehousing, OLAP, data on the web; object-oriented and object-relational systems. CSC446H1
Finite difference methods for hyperbolic and parabolic equations; consistency, convergence, and stability. Finite element methods for 2-point boundary value problems and elliptic equations. Special problems of interest. CSC448H1
Regular, deterministic, context free, context sensitive, and recursively enumerable languages via generative grammars and corresponding automata (finite state machines, push down machines, and Turing machines). Topics include complexity bounds for recognition, language decision problems and operations on languages. CSC454H1
Overview of the software industry, and principles of operation for successful software enterprises. Software business definition and planning; market and product planning; management of innovation, research and software development; software marketing and sales management; software manufacturing and support; financial management of high-technology ventures; human resource management and development in high-technology industries. (Ordinarily offered in alternate years) CSC456H1
Computationally-intensive applications in science and engineering are implemented on the fastest computers available, today composed of many processors operating in parallel. Parallel computer architectures; implementation of numerical algorithms on parallel architectures. Topics from: performance evaluation; scientific visualization; numerical methods; applications from science and engineering. For students in computer science, applied mathematics, science, engineering. CSC457H1
Introduction to complex problem-solving in the pure and applied sciences using numerical methods and high performance computing. Several case studies from current active areas in scientific research are examined as applications of methods in the reduction and analysis of experimental data, numerical simulation of physical phenomena and computer visualization. Emphasis is placed on the optimization and parallelization of algorithms in computationally intensive problems. CSC458H1
Computer communication network design and operation. Representation of information on physical channels; error detection and recovery; local area networks; deadlock and congestion avoidance; internetworking and gateways; network naming and addressing; remote procedures. Emphasis on fundamental principles rather than case studies, but with examples from real networks. CSC465H1
The use of logic as an aid to programming. Formal semantics of programming languages: imperative programs, functional programs, parallel processes, communicating processes. Partial and total correctness. Refinement theorems: by steps, by parts, by cases. Semantics of recursion and the least-fixed-point construction; monotonicity, continuity. Semantics of data types; data refinement. CSC468H1
Principles of operating systems. The operating system as a control program and as a resource allocator. The concept of a process is central: synchronization, mutual exclusion, deadlock. Additional topics include memory management, file systems, process scheduling, and protection. Some treatment of multiprocessor issues, such as threads and scheduling. Case studies from systems such as Unix and Mach. CSC485H1
Computational linguistics and the understanding of language by computer. Augmented context-free grammars, chart parsing, parsing in Prolog. Semantics and semantic interpretation. Ambiguity resolution techniques. Statistical parsing and learning methods for lexical, syntactic and semantic knowledge. Discourse structure and reference resolution. CSC486H1
Representing knowledge symbolically in a form suitable for automated reasoning, and associated reasoning methods: first-order logic, entailment, the resolution method, Horn clauses, procedural representations, production systems, description logics, inheritance networks, defaults and probabilities, tractable reasoning, abductive explanation, the representation of action, planning. CSC487H1
Introduction to vision, visual processes, and image understanding. Brief biological motivation for computational vision. Camera system geometry and image acquisition, basic visual processes for recognition of edges, regions, lines, surfaces. Processing colour, stereo images, and motion in image sequences. Active vision methods such as visual attention and interpretation-guided imaging system geometry changes. Object recognition. Applications of visual systems. CSC488H1
Compiler organization, compiler writing tools, use of regular expressions, finite automata and context-free grammars, scanning and parsing, runtime organization, semantic analysis, implementing the runtime model, storage allocation, code generation. CSC494H1/495H1
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