41 courses with the subject CMSC, 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.
CMSC 111Computer Science Scholars Seminar I1
This course is designed to prepare students in the CS Scholars program for active scholarship by developing the skills needed for college and research success. Students will participate in community-building activities, discuss study and research skills, and practice reading academic papers.
This course is designed to continue preparation for active scholarship by developing the skills needed for academic success in computer science. Students will participate in community-building activities, practice reading academic papers, and practice reviewing and presenting what they have read.
An introduction to computer science for non-specialists. Basic computer architecture and design, storage formats, principles of computer operation, and algorithms. Application software that emphasizes the computer as a tool. Students may not enroll in this course if CMSC 201 has already been completed.
A first course in computer programming, intended for students with no previous experience in writing computer programs. Emphasis will be placed on practical programming skills; assignments will primarily use the Python programming language. Students will cover the fundamental control structures and will learn to process real data stored in sequential lists and in key-value pairs. Students may not enroll in this course if CMSC 160 has already been completed.
An introduction to problem solving and algorithmic design using an object-oriented programming language. Topics include programming logic, iteration, functions, recursion, arrays, memory management, user-defined data types, abstraction, and complexity analysis.
CMSC 161Software Development Tools and Principles1
This class prepares students for advanced work in computer science by exploring the non-programming tools and practices essential to success in computer science. Students will learn to collaborate using agile programming practices, use a text editor to create internal and external documentation, and navigate the Linux command line environment to run programs and edit files. 2 lab hours.
A continuation of CMSC 160 . Topics include algorithmic design, complexity analysis, abstract data types, and encapsulation and basic data structures. Advanced topics using a modern high-level programming language such as inheritance, overloading, and use of objects.
The organization, design, and structure of computer systems, including both hardware and software principles. Topics include memory addressing, machine-level representations of software and data, fundamentals of logic design, and the mechanics of information transfer and control within a computer system.
This course introduces topics in theoretical computer science including formal languages, grammars, and computability, which form the basis for analysis of programs and computation. These tools are then used to explore several modern programming languages and survey the major programming paradigms.
CMSC 160 with a C− or better, MATH 175 ; CMSC 162 recommended
Corequisite
None
CMSC 210Web Page Design and Scripting3
The class will study interactive web pages that provide customized data in response to visitor requests and/or collect data from site visitors. This interaction will be done via program scripts written in an appropriate language.
A hands-on approach to use and administration of the Linux-based operating systems. Emphasizes file systems, process management, account management, software patching and maintenance, text manipulation, and the use of scripts to automate administrative tasks.
CMSC 242Introduction to Network and Systems Programming3
A programming-intensive class covering the fundamentals of operating systems and networking. Emphasizes the use of programming using an Application Programming Interface (API). Topics covered include threading and parallelism, low-level file system access and memory management, communication using signals, socket programming, and the TCP/IP network stack.
CMSC 262Data Structures and Algorithms in Application3
Introduces many of the classic advanced data structures and algorithms in the context of a survey of important applied fields of computer science. Topics include artificial intelligence, relational databases, and human-computer interaction.
A programming-intensive course that gives students a comprehensive introduction to a language not taught in the introductory sequence. Examples of languages which may be taught are Ada, Fortran, and Java. May be repeated for credit when language changes.
CMSC 283Experiential Learning Seminar in Computer Science I0
Active attendance and participation at presentations of internships, directed studies, and other learning experiences by upper-level computer science students. Grading is Pass/Fail.
Independent study of a specific programming language, its syntax and applications, based on prior study of programming languages in general. May not duplicate other language courses. Must be arranged with an instructor and approved by department chair before registering. May be repeated for credit with different languages.
Subject
CMSC
Credits (min)
1
Credits (max)
1
Credit unit
credit
Type
course
Repeatable
May be repeated for credit with different languages.
A semester-long practical learning experience designed to apply the principles of systems administration. The student will be an active maintainer of the department computer lab, network, and servers.
This course will emphasize the practical application of machine learning algorithms across diverse disciplines. Students will explore different machine learning models and learn how to apply them to solve real-word problems using actual datasets. The course will focus on correctly applying and fine-tuning machine learning techniques. Students will build machine learning projects and interpret their results.
CMSC 140 OR Completion of both CMSC 160 and FQRC Pillar
Corequisite
None *Fulfills Civitae Core PQRC SI
CMSC 350Ethical Issues in Mathematics and Computer Science3
Crosslisted With: ( MATH 350 ) Consideration of ethical implications of mathematics and computer science in society. Overview of ethical theory; case studies of situations illustrating ethical dilemmas. A knowledge of calculus and algorithms will be assumed.
CMSC 355Introduction to Computer and Network Security3
A course dealing with basic techniques in computer and network security. Topics covered include elementary cryptography, secure programs, malicious code, protection of operating systems, database security, network security, security administration and legal issues.
CMSC 140 or CMSC 160 and either CMSC 201 or ISCS 371
Corequisite
None
CMSC 360Computer Network Theory3
A course covering the theory and design of modern computer networks. Topics include local and wide area networks, the OSI network model, basic network performance analysis, and real time networks.
A course covering the theory and practice of modern databases design and implementation. Topics include relational and hierarchical database design, database query languages, update consistency, and distributed databases.
This course is designed to introduce students to computer graphics programming techniques. It will combine the use of a high-level programming language with a publicly available graphics application programming interface. Other topics will include the mathematics to manipulate geometric objects.
An introduction to basic concepts in machine learning. Students will be introduced to the fundamental concepts and algorithms used by computers to solve real world problems. Topics include supervised learning (decision trees, logistic regression, neural networks, support vector machines), unsupervised learning (clustering, dimensionality reduction), deep learning, and reinforcement learning. Students will learn and implement various steps of machine learning in practical applications.
A programming intensive course covering the theory and techniques of artificial intelligence (AI) with implementations using both statistical and nonstatistical AI methods. Covered topics will span the central AI problems of planning, learning, and reasoning.
Individualized study; recommended only when material cannot be studied through existing course offerings. Must have permission of department chair. May be repeated when topics change; no more than 6 credits.
Subject
CMSC
Credits (min)
1
Credits (max)
3
Credit unit
credits
Type
course
Repeatable
May be repeated when topics change; no more than 6 credits.
Continues to develop the theoretical frameworks introduced in CMSC 208 such as language and automata theory, and the computability of functions. Topics include complexity analysis through reductions, NP-completeness, hierarchy of languages, and the Church-Turing thesis.
Crosslisted With: ( MATH 420 ) An introduction to topics in graph theory, focusing on analysis of specific applications and proofs of important theorems in the discipline. Topics include graphs, paths, and cycles; directed graphs, trees, and applications of graph theory in real world contexts.
CMSC 140 or CMSC 160 , and either MATH 300 or CMSC 208 .
Corequisite
None
CMSC 442Operating Systems3
A programming-intensive course in which students learn the important data structures and algorithms of an operating system and apply them to the implementation of core O.S. components. Particular focus will be given to problems that arise in the presence of concurrency in both implementation of the operating system and application of programming. Topics include threads, synchronization constructs, I/O and interrupt handling, memory management, addressing, scheduling, and file system design.
A course covering the basic theory and techniques of compiler and code translation systems. Topics include lexical analysis, parsing, and code generation, and the various techniques used when handling differing source language classes. A programming intensive course. Also covered are the techniques of top-down and bottom-up parsing.
This course covers several modern cryptographic systems, including the DES and AES encryption standards. Their applications to network security are discussed, along with issues of authentication, privacy, intruders, malicious programs and firewalls. The approach is from the theoretical side, and the mathematics of these areas is studied.
A capstone course designed to consolidate experiences from a variety of other courses by working in groups on one or more large projects. Principles of software engineering will be covered, including traditional and object-oriented software design, software lifecycle models, software analysis, and management implications. The implementation of developing software using teams will be stressed along with various software tools. Reusability, portability, and interoperability will be discussed. A segment on assessment will be included.
Individualized study; recommended only when material cannot be studied through existing course offerings. Must have permission of department chair. May be repeated for no more than 6 credits.
Students conduct an in-depth project in computer science under the direction of a faculty member and the Longwood Senior Thesis Committee. May be repeated as 499.
