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Students with AP credit for GenEd courses and a strong CS background may take CS 120 and CS 140 in the first semester.
Students without prior programming experience should take CS 110 in fall and either
CS 120 or CS 140 in the spring. Please consult a CS advisor before attempting CS 120
and CS 140 together.
These suggested course tracks are based on undergraduate requirements from the class
entering in the 2019-20 academic year. These are only suggestions, refer to the University Bulletin for the official requirements for each major.
For archived requirements refer to the University Bulletin. Select desired year in the bottom left-hand corner under, "Bulletin Archive" and
then the area of study.
For more information on graduate-level requirements go here.
Take note of pre- or co-requisites.
To receive the BS degree in computer science, the student must earn a minimum of 126
credit hours, including transfer credits, with an average of at least C (2.0 GPA),
and a minimum of a C average in the major program.
Credit Requirements
A minimum of 126 semester credits of which:
- a minimum of 60 credits must be in liberal arts and sciences courses
- a minimum of 40 credits must be earned in Watson School courses
Area Requirements
Communications - 4 credits
- One course that meets the Binghamton University general education composition requirement.
ALSO:
-
CS 301 - Eth Soc & Global Issues Comput
Communications course with required writing and oral presentations. Understanding
the local and global implications of computing in society, including ethical, legal,
security and social issues. Developing professional skills related to computing, including
effective communication and productive teamwork. Fostering an appreciation for continuing
professional development. Should be taken at the same time as or before any junior-level
Computer Science courses. Prerequisites: Any General Education "C" course,
CS 101, and either CS 220 or CS 240. Offered every semester. 4 credits
Levels: Undergraduate
Humanities/social science electives - 20 credits
Science - 12 or 14 credits*
*The total of the science and free elective credits should be 25 credits
- Two-course science sequence:
-
BIOL 113 - Intro to Cell & Molecular
Biol
Introductory Biology: Cell and molecular Biology. Survey of cell and molecular
biology: biological macromolecules, cellular organization and metabolism, cell communication,
cell differentiation, coding of genetic information, inheritance, gene expression
and regulation, cell replication, biotechnology, as well as cellular and molecular
aspects of animal physiology. Lecture and discussion. BIOL 113 and 114 may be taken
in any order. Offered regularly. 4 credits.
Levels: Undergraduate
-
BIOL 114 - Intro to Organisms & Pops
Biol
Introductory Biology: Organisms and Populations. Survey of organismal and population
biology; history of life; structure and physiology of plants and animals; homeostasis,
integration, growth, ecology; animal behavior; evolution. Lecture and discussion.
BIOL 113 and 114 may be taken in any order. Offered regularly. 4 credits.
Levels: Undergraduate
OR
-
CHEM 107 - Intro.Chemistry Principles
I
First of two courses for students who want a one-year, two-semester introductory
general chemistry course as basis for further work in a science. Scientific measurement,
atomic structure, periodic relationships, theories of bonding, states of matter, solution
properties. Lecture and laboratory. Prerequisite: high school chemistry. Not open
to students who have credit for CHEM 111. Credits: 4. Format: 3 hour lecture; 2
hour discussion; 3 hour laboratory per week. Offered: Fall. Course fee applies. Refer
to the Schedule of Classes.
Levels: Graduate, Undergraduate
-
CHEM 108 - Intro Chem Principles II
Continuation of CHEM 107. Thermochemistry and thermodynamics; equilibrium; chemical
kinetics; electrochemistry; nuclear chemistry; descriptive inorganic, organic and
biochemistry.. Prerequisite: CHEM 107 or equivalent. Not open to students who have
credit for CHEM 111. Credits: 4. Format: 3 hour lecture; 2 hour discussion; 3 hour
laboratory per week. Offered: Spring. Course fee applies. Refer to the Schedule of
Classes.
Levels: Undergraduate
OR
-
PHYS 131 - Gen. Physics I(Calculus Based)
A calculus based introduction to the basic concepts underlying physical phenomena,
including kinematics, dynamics, energy, momentum, forces found in nature, rotational
motion, angular momentum, simple harmonic motion, fluids, thermodynamics and kinetic
theory. Lectures, discussion, demonstration, and laboratory. Pre or Co-requisites:
high school trigonometry and algebra; AP calculus or MATH 224/225. 4 credits.
Levels: Undergraduate
-
PHYS 132 - Gen. Physics II(Calculus Based
Fundamentals of electricity, magnetism, light, wave motion and relativity. Lectures,
discussion, demonstration and laboratory. Prerequisite: PHYS 131. Pre or Corequisite:
MATH 226/227. 4 credits.
Levels: Undergraduate
- One science elective: chosen from courses that meet the general education laboratory
science requirement.
Mathematics - 20 credits
-
MATH 224 - Differential Calculus
This is a 2-credit course in differential calculus covering limits, continuity,
and
differentiation. Prerequisites: MATH 223 with a grade of C- or better, or Placement
Exam. Offered each half semester. 2 credits.
Levels: Undergraduate
-
MATH 225 - Integral Calculus
This is a 2-credit course in integral calculus covering optimization and integration.
Prerequisites: MATH 224 with a grade of C- or better. Offered 2nd half of fall semester
and both half semesters of spring semester. 2 credits.
Levels: Undergraduate
-
MATH 226 - Integration Tech & Application
This is a 2-credit course covering the calculus of transcendental & inverse
functions, L’Hospital’s Rule, integral techniques, improper integrals,
calculus of parametric curves, and polar coordinates.
Prerequisites: Math 225 with a grade of at least a C- or consent of instructor. 2
credits.
Levels: Undergraduate
-
MATH 227 - Infinite Series
This is a 2-credit course covering sequences, series, power series, and Taylor
series.
Prerequisites: Math 226 with a grade of at least a C- or consent of instructor. 2
credits.
Levels: Undergraduate
-
MATH 314 - Discrete Mathematics
Logic, sets, relations, functions, induction, recursion, counting methods, graphs,
trees. Some abstract algebra. Prerequisites: C- or better in MATH 225 or consent
of instructor. Every semester. 4 credits.
Levels: Undergraduate
OR
-
MATH 330 - Number Systems
Careful discussion of the real numbers, the rational numbers and the integers,
including a thorough study of induction and recursion. Countable and uncountable sets.
The methodology of mathematics: basic logic, the use of quantifiers, equivalence relations,
sets and functions. Methods of proof in mathematics. Training in how to discover and
write proofs. Prerequisites: C- or better in MATH 227 or MATH 230, or consent of instructor.
Every semester. 4 credits.
Levels: Undergraduate
AND
-
MATH 327 - Probability with Stat Methods
Development of probabilistic concepts in discrete and absolutely continuous cases.
Classical combinatorial methods, independence, random variables, distributions, moments,
transformations, conditioning, confidence intervals, estimation. Open to Watson School
students only. Does not serve as a prerequisite for MATH 448 or for any actuarial
science courses. Prerequisites: C- or better in MATH 227 or MATH 230, or consent of
instructor. Every semester. 4 credits.
Levels: Undergraduate
OR
-
MATH 448 - Mathematical Statistics
Estimation, confidence intervals and hypothesis testing. Introduction to linear
models, categorical data and nonparametric statistics. Students who obtain B- or better
in this course can apply for the VEE Mathematical Statistics credits from Society
of Actuaries. Prerequisites: C or better in MATH 447 and either MATH 314 or MATH 330,
or consent of instructor. Every semester. 4 credits.
Levels: Undergraduate
One elective chosen from:
-
MATH 304 - Linear Algebra
Vector spaces, linear transformations, determinants, characteristic values, inner
products. Prerequisites: C- or better in MATH 225 or consent of instructor. Every
semester. 4 credits.
Levels: Graduate, Undergraduate
-
MATH 371 - Ordinary Diff. Equations
Ordinary differential equations from quantitative and qualitative point of view
including existence and uniqueness theory, first and second order equations and higher
order equations, systems of first order equations, Laplace transforms, series
solutions methods. MATH 371 contains the topics of MATH 324 and includes additional
topics of the theory of existence and uniqueness, and systems of linear equations.
The topics are studied from a more advanced mathematical viewpoint than in MATH 324.
Only one of Math 324 and Math 371 can be counted towards math minor. Prerquisites:
C or better in both MATH 304 and MATH 330, or consent of instructor. Every semester.
4 credits.
Levels: Undergraduate
-
MATH 381 - Graph Theory
Directed and undirected graphs, trees, connectivity, Eulerian and Hamiltonian graphs,
planar graphs, coloring of graphs, graph parameters, optimization and graph algorithms.
Prerequisites: C or better in both MATH 304 and either MATH 314 or MATH 330, or consent
of instructor. Spring only. 4 credits.
Levels: Undergraduate
-
MATH 386 - Combinatorics
Topics from among counting techniques, generating function and recurrence relations,
pigeonhole principle, Ramsey's Theorem, Latin squares, combinatorial designs.
Prerequisites: C or better in both MATH 304 and either MATH 314 or MATH 330, or consent
of instructor. Fall only. 4 credits.
Levels: Undergraduate
-
MATH 407 - Intro to the Theory of Numbers
Classical number theory. Divisibility, prime numbers, quadratic reciprocity, Diophantine
equations. Prerequisites: C or better in MATH 330, or consent of instructor. 4 credits.
Levels: Undergraduate
Free electives - 11 or 13 credits*
*The total of the science and free elective credits should be 25 credits
At least four credits must be in liberal arts and science. At most one free elective
in liberal arts and science may be taken pass/fail instead of a letter grade. At most
2 credits of activity/wellness may be used as free elective credit.
Computer Science - 57 credits
-
CS 101 - Prof Skills Ethics & CS Trends
Introduction to and discussion of topics of interest to computer science majors:
social, ethical and professional issues; university, school and department resources;
current developments in computer science. Prerequisite: none. Offered in the Fall
semester. 1 credits
Levels: Undergraduate
-
CS 120 - Prog & Hardware Fundamentals
Introduction to the C programming language, including local and global variables,
basic control structures, function calls, pointers and the stack; use of command-line
C development environments and development tools such as gdb and make; assembly language
connection to higher-level C; building blocks of the Von Neumann machine (ALU, registers,
control unit, RAM, decoders, program counters) and the underlying basic logic elements;
simple non-pipelined processor architectures. Supervised laboratory work involves
programming in C and low-level languages, interfacing with hardware, and the design
and simulation of small circuits and simplified microprocessors. Prerequisite MATH
225 that may be taken concurrently. Prerequisite: CS 110, CS Majors may request a
waiver from the Undergraduate Director based on prior programming experience. Offered
every semester. 4 credits
Levels: Graduate, Undergraduate
-
CS 140 - Prog with Obj & Data Struct
Assumes a foundation in procedural programming as covered in CS 100 or CS 110.
Provides the foundations of software development using Java. Problem solving using
object-oriented programming techniques is emphasized. Topics include primitive and
reference data types, variables, expressions, assignment, functions/methods, parameters,
selection, iteration, recursion, exception handling, generic linear data structures
and maps, file types, file I/O, simple GUIs, programming to an interface, use of inheritance,
javadoc documentation, and introduction to Java threads. Required laboratory provides
supervised problem solving, programming using the command line as well as Eclipse
or Netbeans development environments, code backup in a version control repository,
debugging and JUnit testing techniques. Prerequisite: CS 110,CS Majors may request
a waiver from the Undergraduate Director based on prior programming experience. Offered
every semester. Prerequisite math 225 (All prerequisites must have a grade of C- or
better).
Levels: Graduate, Undergraduate
-
CS 220 - Arch from a Prog Perspective
The architecture and programming of computer systems. Data representation and computer
arithmetic. Processor and memory organization. Assembly and machine language programming.
Advanced C programming language constructs and their implementation in assembly language.
Introduction to system software (assemblers, linkers, loaders, compilers). Supervised
laboratory work involves programming and debugging using machine language, assembly
language and C. Prerequisite: CS 120 and CS 140 (All prerequisites must have a grade
of C- or better). Offered every semester. 4 credits
Levels: Graduate, Undergraduate
-
CS 240 - Data Struct & Algorithms
Analysis of the design, implementation, and properties of basic and advanced data
structures, including lists, stacks, queues, hash tables, trees, heaps, and graphs.
Design and time-space analysis of basic and advanced algorithms, including searching,
sorting, insert/delete, hash table collision resolution techniques, recursive functions,
balanced tree maintenance, and graph algorithms. Weekly required laboratory programming
and three or more additional programming projects in C++. Practical programming techniques
including C++ templates and the Standard Template Library (STL), operator overloading,
C++ stream I/O, separate compilation using makefiles, debugging tools and techniques,
dynamic memory management. Prerequisites: CS 120 and CS 140, and either MATH 226 (may
be taken concurrently) OR MATH 230 (All prerequisites must have a grade of C- or better).
Offered every semester. 4 credits
Levels: Graduate, Undergraduate
-
CS 320 - Advanced Computer Architecture
Performance metrics and analysis; instruction set architecture and its implications;
high-performance computer arithmetic; instruction pipelines and pipelined datapath
implementation; out-of-order execution, register renaming, branch prediction and superscalar
processors; caches and memory systems; memory hierarchy; the I/O subsystem; reliable
storage systems; introduction to multicore and multithreaded architectures; introduction
to GPUs and accelerators. Required lab includes programming projects. Prerequisite:
CS 220. Offered every semester. 4 credits
Levels: Undergraduate
-
CS 350 - Operating Systems
Introduction to the design and implementation of operating systems: hardware/software
interface; processes and threads; CPU scheduling; virtual memory; memory management;
concurrency, race conditions, deadlocks, and synchronization; file and storage systems;
input/output; protection and security; virtualization and hypervisors; multi-processor
operating systems. Required lab includes programming exercises and presentations.
Prerequisites: CS 220 and CS 240 (All prerequisites must have a grade of C- or better).
Prerequisite (May be taken concurrently.): CS 301. Offered every semester. 4 credits.
Levels: Undergraduate
-
CS 373 - Automata Theory & Formal
Lg.
Theory and application of automata and the languages they recognize. Regular languages,
finite-state automata, regular expressions, context-free languages, normal forms,
pushdown automata, context-sensitive languages, linear bounded automata, Turing machines,
computability, transducers. Application of concepts. Required activity includes student
presentations. Prerequisites: CS 140 and either MATH 314 or MATH 330 (All prerequisites
must have a grade of C- or better). Offered every semester 4 credits
Levels: Undergraduate
-
CS 375 - Design & Analysis of Algorithm
Analysis of common algorithms for processing strings, trees, graphs and networks.
Comparison of sorting and searching algorithms. Algorithm design strategies: divide
and conquer, dynamic, greedy, back tracking, branch and bound. Introduction to NP-completeness.
Required activity includes student presentations. Prerequisites: CS 240, MATH 227
and MATH 314 or MATH 330, CS 301 (may be taken concurrently). (All prerequisites must
have a grade of C- or better). Offered every semester. 4 credits
Levels: Undergraduate
-
CS 471 - Programming Languages
Introduction to the design and implementation of programming languages: linguistic
features for expressing algorithms; formal syntax specification; introduction to language
semantics and parsing; declarative programming (functional and goal-driven); scripting
languages; imperative programming (procedural and object-oriented); comparative design
and implementation issues across languages and paradigms. Assignments emphasize languages
such as Prolog, Haskell, Python, and Ruby. Required lab includes student presentations.
Prerequisites: CS 373 and 375 (All prerequisites must have a grade of C- or better).
Offered every semester. 4 credits
Levels: Undergraduate
Four Computer Science electives chosen from A, B, C, and D below. At least one must
be chosen from A and at least one from B. At most one can be taken from D.
A.
-
CS 428 - Computer Networks
Communication protocols and layering, hardware-software infrastructures for networking,
MAC protocols, data link protocols, switching, inter- and intra-domain routing, the
TCP/IP protocol suite, transport protocols, application layer protocols, local and
system area networks, wireless and sensor networks, overlay and virtual networks,
client-server and peer-to-peer models, network programming with sockets, protocol
design and implementation issues, network security. Prerequisite: CS 350 (All prerequisites
must have a grade of C- or better). Term offered varies. 4 credits.
Levels: Undergraduate
-
CS 451 - Systems Programming
A detailed study of the application program interface of a modern operating system.
File operations, concurrency, processes, threads, inter-process communication, synchronization,
client-server programming, multi-tier programming. Prerequisite: CS 350 (All prerequisites
must have a grade of C- or better). Term offered varies. 4 credits
Levels: Undergraduate
-
CS 457 - Intro To Distributed Systems
Fundamental issues in distributed systems. Distributed synchronization and concurrency
control. Distributed process management (scheduling, remote invocation, task forces,
load balancing). Protection and security. Robust distributed systems. Case studies.
Prerequisites: CS 350 (All prerequisites must have a grade of C- or better). Term
offered varies. 4 credits
Levels: Undergraduate
-
CS 476 - Program Models Emerg Platforms
The landscape of computation platforms has changed dramatically in recent years.
Multi-core CPUs, CUDA-enabled game chips, and Android-powered smartphones are widely
available to millions of users, but programming on these emerging platforms remains
a challenging task. This course introduces a number of state-of-the-art programming
models on these platforms, and further explores the frontier of next-generation programming
language design that may potentially impact the future programming practice for emerging
platforms. In particular, the course investigates multi-core programming, GPGPU programming,
and Android programming. Applications of these programming models range from high-performance
computing, games, to energy-conscious systems. Prerequisites: CS 140, CS 320 and CS
350 (All prerequisites must have a grade of C- or better). Term offered varies.
4 credits
Levels: Undergraduate
B.
-
CS 440 - Adv Topics - Obj Oriented Prog
Object-oriented programming and its concomitant design patterns provide rich abstractions
for program development. These programs will eventually execute on real hardware,
however. This course will investigate advanced object-oriented techniques and how
they interact with hardware and operating system issues. We will ground our topics
in C++, but the goal of the course will be to develop understanding that can be applied
across languages. We will examine different design techniques for things such as memory
management, and explore how and why they differ in performance and robustness. We
will also cover idioms such as "Resource Acquisition Is Initialization"
(RAII) and how they can be used to provide robust resource management for exceptions
(exception safety). We will also devote time to covering generic programming and related
topics such as expression templates. This is a growing area that seeks to decouple
algorithms and data structures through the use of templates and other meta-programming
techniques. These techniques exploit the fact that the C++ template mechanism is a
language-within-a-language that is executed at compile-time rather than run-time.
Additional topics include dynamic linking for techniques such as "plug-ins",
template instantiation mechanisms, template specialization, idioms for memory management,
thread-safety issues, thread-safety, C++ reflection. Prerequisites: CS 240 and CS
350.
Levels: Undergraduate
-
CS 442 - Design Patterns
Patterns for program design including examples of patterns used in existing software
libraries. Exercises in programming with design patterns and communicating designs
to other programmers using the language of patterns. Use of an object-oriented programming
language to implement patterns and principles for common design problems. Design patterns
are applied to problems involving features including concurrency, sockets, streams,
reflection, and dynamic proxies. The course also discusses automating software build
processes with build tools.
Prerequisites: CS 140 and CS 375 (All prerequisites must have a grade of C- or better).
Term offered varies. 4 credits
Levels: Undergraduate
-
CS 444 - Programming for the Web
An in-depth understanding of programming for the World Wide Web: detailed
coverage of widely used language(s) for web programming, asynchronous programming,
principles of
web architecture, web protocols, web design patterns, client-side programming, templating,
server-side
programming, a technical history of the web, web security. Students are expected to
have experience
with a modern programming language and will be assigned programming projects using
current state-of-
the-art web technologies.
Prerequisite: CS 320 or CS 350 or CS 375. 4 credits
Levels: Undergraduate
-
CS 445 - Software Engineering
Software engineering practice applied to the life cycle of software applications
and engineering projects. Software project planning and management: risk management,
estimation, scheduling, trade studies, CM and SQA. Software development: process model
selection, domain analysis, requirements gathering, analysis and design modeling,
user interface design, architectural and detailed design, documentation, testing strategies/methods,
test plan generation, and reuse. Advanced topics include formal methods and cleanroom
software engineering. Requires a major team project. Prerequisites: CS 350 or CS 375
(All prerequisites must have a grade of C- or better). Term offered varies. 4 credits
Levels: Undergraduate
-
CS 472 - Compiler Design
Fundamentals of programming language translation. Compiler design concepts. General
aspects of lexical analysis and parsing of context-free languages. Grammars and parsing
techniques. Syntax-directed translation. Declarations and symbol management. Semantic
processing and code generation. Principles, methods and examples of code optimization.
Prerequisite: CS 373 and CS 375 (All prerequisites must have a grade of C- or better).
Term offered varies. 4 credits
Levels: Undergraduate
C.
The following courses and CS 400-level courses approved for future catalog years.
-
CS 402 - Software & Eng. Project Mgmt
Information is traveling faster and being shared by more individuals than ever
before. Although project management has been an established field for many years,
managing Software Development and Information Technology Projects requires ideas and
information that go beyond standard project management. This course presents an understandable,
integrated view of the many concepts skills, tools, and techniques involved in software
project management. The Project Management Knowledge areas (from PMI’s PMBOK)
are used to guide the student through the concepts of Software Project Management
techniques and their application to the management of software and IT projects. Specifically,
students will learn how to develop a software development plan including its associated
tasks, milestones and deliverables, software project scheduling and how/why to establish
relationships among the different tasks. Prerequisites: CS 220 and CS 240 Junior or
Senior standing in Computer Science or Information Systems, or CS 211 and CS 212 and
Junior or Senior standing in Computer Engineering
Levels: Undergraduate
-
CS 424 - Microcontrollers And Robotics
Microprocessor-based systems in hardware control. Embedded microcontroller systems:
architectures and instruction sets for microprocessors and microprocessor-based control
systems; memory and I/O port organization; serial and parallel I/O; timers; interrupts;
ADC; DAC. Robotics: hardware; software; motion control; interaction control; actuators
and sensors; trajectory planning; navigation; image processing and vision systems;
operating systems and programming languages; multitasking; robot behavior and intelligence
architectures; robot kinematics and dynamics. Supervised laboratory work involves
microprocessor programming, interfacing and hardware control experiments. Students
working in teams design and build mobile, autonomous, microprocessor-controlled robots
and program them to perform a variety of tasks. Prerequisite (May not be taken concurrently
) : CS 350. Term offered varies. 4 credits
Levels: Undergraduate
-
CS 426 - Internet of Things
Wireless sensor networks contain a large number of self-organizing communication
devices. Each device has sensing, actuation, and wireless communication capability,
as well as a certain level of intelligence for signal processing. Wireless sensor
networks have been used in many applications such as personal communication, military
surveillance, habitat monitoring and scientific exploration. The hype indicates that
wireless sensor networks will dominate every aspect of our lives in the near future.
This class presents the fundamentals regarding the hardware and software of wireless
sensor networks. It synthesizes materials from many research papers, presenting principles,
commonalities and open research issues. In this course, students will also have an
opportunity to obtain hands-on experience on programming tiny communication devices
to sense and communicate. Topics covered include: the introduction of sensor networks
research; sensor network applications; programming sensor nodes by using TinyOS, NesC
and TOSSIM; wireless networking protocols; wireless media access control; middleware
(including time synchronization, localization, power management), security and privacy
in wireless sensor networks. Prerequisites: CS 350
Levels: Undergraduate
-
CS 432 - Database Systems
Associations between data elements and data models: entity-relationship, relational
and object-oriented. Relational database design techniques. Formal and commercial
query languages. Introduction to query processing, transaction management and concurrency
control. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better).
Term offered varies. 4 credits
Levels: Undergraduate
-
CS 433 - Information Retrieval
Indexing and data structures for storing and searching the index. Boolean, statistical,
inference nets and knowledge-based models. Thesaurus construction. Query expansion.
Natural language and linguistic techniques. Evaluation. Distributed information retrieval.
Information integration and fusion. Dissemination of information. Summaries, themes
and reading tours. Hypertext. Internet tools. Intelligent agents. Digital libraries.
Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term
offered varies. 4 credits
Levels: Undergraduate
-
CS 435 - Introduction To Data Mining
Basic topics of data mining, including data preprocessing, mining association rules,
classification rules, clustering rules, post processing and mining in unstructured
data. Prerequisites: CS 375, MATH 304 and MATH 327 or MATH 448 (All prerequisites
must have a grade of C- or better). Term offered varies. 4 credits
Levels: Undergraduate
-
CS 436 - Intro to Machine Learning
This course provides a broad introduction to machine learning and its applications.
Major topics include: supervised learning (generative/discriminative learning, parametric/non-parametric
learning, support vector machines); computational learning theory (bias/variance tradeoffs,
VC theory, large margins); unsupervised learning; semi-supervised learning; reinforcement
learning. The course will give students the basic ideas and intuition behind different
techniques as well as a more formal understanding of how and why they work. The course
will also discuss recent applications of machine learning, such as to data mining,
bioinformatics, and information retrieval. Prerequisites: CS 375 and MATH 327 or MATH
448 (All prerequisites must have a grade of C- or better). Term offered varies.
4 credits
Levels: Undergraduate
-
CS 441 - Game Devel for Mobile Platform
This course focuses software development for mobile computing platforms, such as
smartphones and tables, with an emphasis on games. Students will develop interactive
applications, and utilize the wide variety of sensors and networking features available
on the platform, along with basic elements of graphics programming and animation.
The course also covers the mechanics of distributing software for mobile computing
platforms. Both iOS and Android operating systems will be covered. The course will
feature a mix of individual and team projects. Prerequisite: CS 140 , CS 375. (All
prerequisites must have a grade of C- or better). Term offered varies. 4 credits.
Levels: Undergraduate
-
CS 455 - Intro to Visual Info Processin
The course focuses on fundamental topics, including visual information acquisition,
representation, description, enhancement, restoration, transformations and compressions,
and reconstruction from projections. The second focus is on Computer Science applications,
including algorithms developed in applications such as statistical and syntactic pattern
recognition, robotic vision, multimedia indexing, visual data mining, and bio-informatics.
Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term
offered varies. 4 credits
Levels: Undergraduate
-
CS 456 - Intro to Computer Vision
Course has two parts. Part one focuses on an introduction to the fundamental topics
of
computer vision, including low-level vision, intermediate-level vision, high-level
vision, vision systems, visual
knowledge representation, motion analysis, shape from shading and 3D reconstruction,
as well as image
retrieval. Part two introduces the applications of the fundamental computer vision
techniques. Examples include
robotic vision, pattern recognition and medical imaging. Pre req CS 375. 4 credits
Levels: Undergraduate
-
CS 458 - Intro to Computer Security
The course provides an introduction to the principles and practices of network,
computer, and information security. Topics include authentication and cryptographic
techniques, intrusion detection, access control, security policies, and program/policy
analysis techniques. Prerequisites: CS 350 and CS 375 (All prerequisites must have
a grade of C- or better). Term offered varies. 4 credits
Levels: Undergraduate
-
CS 459 - Science of Cyber Security
This course focuses on techniques that approach cyber security problems in a principled
manner using concepts from data mining, game theory, graph theory, and psychology.
The intent of this course is to permit students to bridge the divide between real-world
cyber threats and formal, scientific foundations of solutions that address such threats.
Real-world cyber security issues, such as spamming, phishing attacks, malware, sybil
attacks in social networks, and DDoS attacks, are used to illustrate how cyber threats
can be modeled with abstract representations that are amenable to rigorous analysis
and formal reasoning. The course also emphasizes the development of cyber defense
mechanisms that are rooted in scientific foundations. Prerequisite: CS 350 and CS
375. 4 credits.
Levels: Undergraduate
-
CS 460 - Computer Graphics
Concepts, structure, techniques and algorithms for use of modern interactive computer
graphics systems. Graphics hardware, software system structure. Techniques and algorithms
for basic graphics input/output functions. Matrix techniques for transformations and
projections. Techniques for two- and three-dimensional modeling, rendering, animation
and visualization. Prerequisite: CS 375 (All prerequisites must have a grade of C-
or better). Prerequisite or Corequisite: MATH 304. Term offered varies. 4 credits
Levels: Undergraduate
-
CS 465 - Intro to Artificial Intelligen
This course will cover the basic ideas and techniques underlying the
design of artificial intelligence (AI) agents. Topics include search,
knowledge representation (and reasoning), planning, reasoning under uncertainty, machine
learning (including reinforcement learning), and applications (natural language processing,
vision, robotics, etc). Pre reqs CS 375
Levels: Undergraduate
Prerequisites vary by course
D.
To count as a CS elective, must be taken for 4 credits
CS 395. Computer Science Internship. Prerequisites: CS 220, 240, junior or senior
standing and CS Department approval
CS 396. Computer Science Co-op. Prerequisites: CS 220, 240, junior or senior standing
and CS Department approval
CS 499. Undergraduate Research. Prerequisites vary by research area. Requires junior
or senior standing and CS Department approval
General Education Requirements
Students must fulfill the general education requirements for computer science. Students
normally complete these requirements within the 126-credit program described above.
Supplemental information regarding the BSCS Degree Requirements
The following information supplements that provided in the University Bulletin. It
applies to students who matriculated Fall 2016 or after.
All required Computer Science courses, except CS 101, are offered every semester.
The minimum grade in a required Computer Science course must be at least a C- to be
allowed to take any Computer Science course, for which it is a prerequisite.
Calculus topics are broken down as follows:
-
MATH 224 - Differential Calculus
This is a 2-credit course in differential calculus covering limits, continuity,
and
differentiation. Prerequisites: MATH 223 with a grade of C- or better, or Placement
Exam. Offered each half semester. 2 credits.
Levels: Undergraduate
-
MATH 225 - Integral Calculus
This is a 2-credit course in integral calculus covering optimization and integration.
Prerequisites: MATH 224 with a grade of C- or better. Offered 2nd half of fall semester
and both half semesters of spring semester. 2 credits.
Levels: Undergraduate
-
MATH 226 - Integration Tech & Application
This is a 2-credit course covering the calculus of transcendental & inverse
functions, L’Hospital’s Rule, integral techniques, improper integrals,
calculus of parametric curves, and polar coordinates.
Prerequisites: Math 225 with a grade of at least a C- or consent of instructor. 2
credits.
Levels: Undergraduate
-
MATH 227 - Infinite Series
This is a 2-credit course covering sequences, series, power series, and Taylor
series.
Prerequisites: Math 226 with a grade of at least a C- or consent of instructor. 2
credits.
Levels: Undergraduate
Humanities/Social Science – May be filled by courses offered by the Division of Humanities, the Division of
Social Sciences, the Psychology Department and HDEV courses offered by the College
of Community and Public Affairs. Many of the courses taken to meet the general education
requirements will fulfill the humanities/social science requirement.
Mathematics - Students who are strong in math are encouraged to take MATH 330 (Number Systems)
instead of MATH 314 (Discrete Mathematics). Students with a strong math background
may take MATH 381 (Graph Theory) as their Math elective. The following course can
be substituted for MATH 327: MATH 448 (Introduction to Probability and Statistics
II), which has a prerequisite of MATH 323 and MATH 447.
Free Electives – May be filled by extra courses from any of the areas listed above, SOM courses, or
additional computer science courses. A maximum of two HWS credits may be counted as
free elective credits. At least four of these credits must be in humanities, social
sciences, arts and other disciplines (excluding computer science) that provide breadth
of background. CS 110 counts as a free elective.
Prerequisites for Computer Science Courses
The MATH and CS pre-requisites must have a grade of at least C-.
- CS 101: None
- CS 110: MATH 225
- CS 120: CS 110, MATH 225
- CS 140: CS 110, MATH 225
- CS 220: CS 120, 140
- CS 240: CS 120, 140, MATH 226
- CS 301: CS 101, Gen Ed C course, CS 220/CS 240
- CS 320: CS 220
- CS 350: CS 220, 240, 301
- CS 373: CS 140, MATH 314/330
- CS 375: CS 240, MATH 227, 314/330, CS 301
- CS 402: CS 220, 240
- CS 424: CS 350
- CS 426: CS 350
- CS 428: CS 350
- CS 432: CS 375
- CS 433: CS 375
- CS 435: CS 375, MATH 304, 327/448
- CS 436: CS 375, MATH 327/448
- CS 440: CS 240, 350
- CS 441: CS 140, 375
- CS 442: CS 140, 375
- CS 443: CS 320, 350
- CS 444: CS 320/CS 350/CS 375
- CS 445: CS 350/375
- CS 451: CS 350
- CS 455: CS 375
- CS 457: CS 350
- CS 458: CS 350, 375
- CS 459: CS 375, MATH 327/448
- CS 460: CS 375
- CS 465: CS 375
- CS 471: CS 373, 375
- CS 472: CS 373, 375
- CS 476: CS 140, 320, 350