43 courses with the subject CS, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
CS 105An Introduction to Computer Concepts
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: This course presents an overview of the role of computers in society: their application and misapplication, their capabilities and limitations. Applications may include artificial intelligence, medical, aerospace and business use of computers. Computer hardware and associated technologies are discussed. Computer programming is taught from a non- mathematical, problem-solving point of view; the course objective is to help students acquire an understanding of the programming process, rather than to develop complex or extended computer programs. Course Note: This survey course is not part of the computer science major sequence. Students planning to major in computer science should start with CS 110. Distribution Area: Mathematics and Technology Enrollment Requirements: Prerequisite: MATH 115 or appropriate math placement score Course Catalog ID: 013054 Course Offer Number: 1
CS 107AI for All: A Non-Technical Introduction to Artificial Intelligence
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: A basic knowledge of AI and the confidence to assess its applications have become important skills for students. In addition to shaping the future in many industries, from health care to education to finance, that interest our students, AI systems raise important questions about the reliability and privacy of data, as well as about ethics, creativity, the environmental cost of technology, and the responsibilities of government. This course serves as a general introduction to these varied applications and to the larger questions they raise. The learning goals of the course include an introduction to machine learning and algorithmic computation, but the larger objective is to make students reflect on how they use data, make decisions, and solve complex problems, as 563
Advanced Physics Courses (9 to 11 Credits) PHYSIC 421 - Atomic Physics and Introduction to Quantum Mechanics • Two additional PHYSIC courses at the 300-level or higher.
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: An introductory course in Java programming that exposes students to the concepts involved in using a higher-level, object-oriented programming language. The course will explain the program development process and give students lots of hands-on experience writing small Java programs. Course Note: The course serves as a prerequisite to other IT courses. CS 114L and IT 114L are the same course. This course is cross-listed as: IT 114L Distribution Area: Mathematics and Technology Enrollment Requirements: Prerequisite: MATH 115 or higher or placement into MATH 130 or higher Course Catalog ID: 013182 Course Offer Number: 1
Formerly: CS 210L Credit(s): 4 Component(s): Lecture and Discussion Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: The design and implementation of computer programs in a high-level language, with emphasis on proper design principles and advanced programming concepts, including dynamic data structures and recursion. The assignments are designed to introduce the student to a variety of topics in computing: data structures and ADTs, Lists, Stacks, Queues, Ordered Lists, Binary Trees, and searching and sorting techniques. 567
Formerly: CS 320L Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: An introduction to the mathematical structures and concepts used in computing: sets, mathematical induction, ordered sets, Boolean algebras, predicate calculus, trees, relations and lattice theory. Formal and informal theories and corresponding mathematical proofs are taught. Course Note: Students may not receive credit for both MATH 320 and CS 220. Students may not take MATH 320 to receive a better grade in previously taken CS/MATH 320L. Enrollment Requirements: Prerequisites: CS 110 and MATH 140 or permission of instructor Course Catalog ID: 013080 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: Cognitive science is an interdisciplinary field fundamentally concerned with furthering our understanding of the development, underlying processes, and implementation of language, perception, problem-solving, learning, memory, and other intelligent capacities. This course offers an introduction to this science for all levels of undergraduate majors in psychology, computer science, biology, and other related fields. Course Note: CS 271L and PSYCH 271L are the same course. This course is cross-listed as: PSYCH 271L Distribution Area: Social and Behavioral Sciences Course Catalog ID: 031681 Course Offer Number: 2
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: Blockchain enables a digital decentralized society where people can contribute, collaborate, and transact without having to second-guess trust and transparency. It is the technology behind the success of Bitcoin, Ethereum, and many disruptive applications and platforms that have impact in numerous sectors, including finance, education, health care, environment, transportation, and philanthropy, to name a few. This course covers a basic set of essential concepts, algorithms, and tools suitable for aspiring students who want to be technologically ready for a blockchain venture. Topics touch various issues in decentralized computing and networking. Students will learn programming skills sufficiently to develop a blockchain project from scratch. Enrollment Requirements: Prerequisite: CS 310 or permission of instructor Course Catalog ID: 041675 Course Offer Number: 1
CS 420An Introduction to the Theory of Computation
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: This course introduces such theoretical aspects of computing as models of computation, inherent limits on computation, and feasible computation. Topics include definition of computable functions (recursive functions, functions computable by Turing machines, functions computable in a programming language), unsolvability of the halting problem and related problems, the classes P and NP, finite automata, and context-free grammars. Enrollment Requirements: Pre-requisite: CS 220 (grade of C- or better) Semester(s) typically offered: Fall Spring Course Catalog ID: 013088 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (no P/F option) Repeatable for credit: Not repeatable Description: Indexing and query optimization in database systems. Writing programs to update database. ACID properties. Concurrency theory: serializability, 2-phase locking, deadlock detection. Transactional Recovery: REDO and UNDO logging, different checkpoint approaches, media recovery. Examples of recovery utility use in INGRES, ORACLE and DB2. Transactional performance: the TPC-A benchmark, analysis of bottlenecks, and cost-performance considerations. Distributed database systems. Two-phase commit. Database parallelism. Course Note: This course is an undergraduate version of CS 634 and is co-taught with it. You may not recei Knowledge of C++ and Java, data structures, and algorithms is required. Enrollment Requirements: Prerequisites: CS 310 and CS 430 / CS 630 consent required for enrollment: Instructor Semester(s) typically offered: Fall and Spring Course Catalog ID: 043030 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: A study of database applications, that is, software systems that solve a particular real-world problem and hold their data in a relational database. The systems under study will also have a realistic user interface. Students will work in small groups on a real-world project specified and implemented during the term. Topics include system specification from user needs, analysis of dataflow and workflow, object design, database design, and client-server techniques. Enrollment Requirements: Prerequisites: CS 310 and CS 430 Course Catalog ID: 035493 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: This course presents the practical side of machine learning for applications, such as pattern recognition from images or building predictive classifiers. Topics will include linear models for regression, decision trees, rule based classification, support vector machines, Bayesian networks, and clustering. The emphasis of the course will be on the hands-on application of machine learning to a variety of problems. Course Note: This course does not assume any prior exposure to machine learning theory or practice. Enrollment Requirements: Prerequisite: CS 310 Course Catalog ID: 039054 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: Mobile devices are becoming ubiquitous along with the high demand for mobile applications serving corporations and millions of end-users. In this course, students will learn programming skills for developing mobile applications on the Android platform, which is the fastest growing mobile operating system. Android is open source and includes many libraries that can help developers easily implement rich and complex applications. Students in this course will learn how to create, test,and deploy Android applications. Course Note: Solid skills of Java programming and application development are necessary for successful completion of this course. Enrollment Requirements: Prerequisite: CS 310 Course Catalog ID: 038755 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: The objective of this course is to provide a practical understanding of computer networks, with emphasis on the Internet. The course starts with an overview of the Internet, its protocol layers, edge and core networks, access networks and physical media. The course then focuses on fundamental design and implementation concepts of the application, transport, and network layers of the Internet. Enrollment Requirements: Course Catalog ID: 013094 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Not repeatable Description: After completing this course, you will be able to develop rich and interactive web- based 3D visualizations for computers, smartphones, and tablets. By using WebGL, you will learn to create immersive and high-quality graphics, including 3D geometric transformations, camera transformations, the image-rendering process, as well as materials and texture mapping. This course also includes advanced topics such as color representations, light simulation, dealing with geometries, and creating animations. And since everything runs in the browser, you can show your work to your friends with a link to a website. Enrollment Requirements: Prerequisites: CS 310 and MATH 260 Course Catalog ID: 013095 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Repeatable - total credits: 999 / total completions: 99 Description: An advanced course offering intensive study of selected topics in computer science. Course content varies and will be announced prior to registration. Course Catalog ID: 013099 Course Offer Number: 1
Credit(s): 3 Component(s): Lecture Grading Basis: Graded (includes P/F option) Repeatable for credit: Repeatable - total credits: 9 / total completions: 3 Description: The design and execution of a significant research project under the guidance of a faculty advisor. Successful completion and oral defense of the thesis is necessary to qualify for Honors in Computer Science. Course Note: Both the instructor and the project must be chosen and approved prior to the start of the course. Offered every semester. Enrollment Requirements: Prerequisites: CS 310 and CS 420 Course Catalog ID: 013104 Course Offer Number: 1
