Course Descriptions

This is a listing of the all courses offered by the HMC computer science department. For a graphical depiction of course precedence, see the course precedence diagram. To see the courses we are offering in the current semester, visit the class schedule.

Please note that this page is offered only for your convenience. For the most up-to-date information on our courses please see the official Harvey Mudd College course catalog. While we make every effort to ensure that the information on this page is accurate, the official course catalog should be considered authoritative if there is any conflict between it and the information on this page.

Note: Please be sure to check all prerequisites in the catalog when choosing your courses as some subtleties may not be reflected here. In particular, when checking the math prerequisites please bear in mind that this page includes only the HMC course numbers but the equivalent courses offered by the math departments at the other Claremont Colleges often use different course numbers.

To see descriptions of the courses offered by the Mathematical and Computational Biology Major, please refer to the Harvey Mudd College course catalog.

CS 5. Introduction to Computer Science

Prerequisites
Permission of instructor

Credit Hours
3.0

Offered
Fall semester

Introduction to elements of computer science. Students learn computational problem-solving techniques and gain experience with the design, implementa­tion, testing, and documentation of programs in a high-level language. In addition, students learn to design digital devices, understand how computers operate, and learn to program in a small machine language. Students are also exposed to ideas in computability theory. The course also integrates societal and ethical issues related to computer science.

Access to CS 5 for students from other Claremont Colleges varies by semester and enrollment is handled through PERM requests. Additional information can be found on our page for off-campus students.

CS 5GR. Introduction to Biology and Computer Science

Prerequisites
Permission of instructor

Credit Hours
3.0

Offered
Fall semester

This course introduces fundamental concepts from the Core course CSCI005 HM using biology as the context for those computational ideas. Students see both the intellectual and practical connections between these two disciplines and write computer programs to explore biological phenomena. Biology topics include the basics of bio­chemistry, the central dogma, population genetics, molecular evolution, metabolism, regulation, and phylogenetics. Computer science material includes basic data types and control structures, recursion, dynamic programming, and an introduction to automata and computability.

This course fulfills the computer science Core requirement at Harvey Mudd College. It does not fulfill the Harvey Mudd biology Core requirement.

CS 35. Computer Science for Insight

Prerequisites
CS 5 or CS 5GR

Credit Hours
3.0

This course extends CSCI005 HM in developing software-composition skills. Pairing lectures and lab sessions, the experience will deepen foundations in algorithms and data structures, introduce machine learning and its mindset, weigh tradeoffs between human- and machine-efficiency, and build sophistication in software, both assembling existing software packages and from-scratch design. Students will deploy and assess computing projects of their own design — with substantive application beyond CS itself — as the course’s final capstone. The course continues in the language of CSCI005 HM and especially encourages computing efforts which contribute to fields of interest beyond CS, whether academic or extracurricular.

CS 42. Principles and Practice of Computer Science

Prerequisites
Permission of instructor

Credit Hours
3.0

Offered
Fall semester

Accelerated breadth-first introduction to computer science as a discipline for students (usually first-year) who have a strong programming background. Computational models of functional, object-oriented, and logic programming. Data structures and algorithm analysis. Computer logic and architecture. Grammars and parsing. Regular expressions. Computability. Extensive practice constructing applications from principles, using a variety of languages.

Successful completion of this course satisfies the CSCI005 HM core requirement and CSCI060 HM coursework.

CS 60. Principles of Computer Science

Prerequisites
CS 5 or CS 5GR

Credit Hours
3.0

Offered
Fall and Spring

Introduction to principles of computer science. Information structures, functional programming, object-oriented programming, grammars, logic, logic programming, correctness, algorithms, complexity analysis, finite-state machines, basic processor architecture, and theoretical limitations.

Those who have completed CSCI042 HM cannot take CSCI060 HM.

CS 70. Data Structures and Program Development

Prerequisites
(CSCI042 HMC or CSCI042 HM) and at least one mathematics course at the level of calculus or higher; Math055 recommended

Credit Hours
3.0

Offered
Fall and Spring

Abstract data types including priority queues and dynamic dictionaries and efficient data structures for these data types, including heaps, self-balancing trees, and hash tables. Analysis of data structures including worst-case, average-case and amortized analysis. Storage allocation and reclamation. Secondary storage considerations. Extensive practice building programs for a variety of applications.

CS 81. Computability and Logic

Prerequisites
MATH055 HM and (CSCI060 HM or CSCI042 HM)

Credit Hours
3.0

Offered
Fall and Spring

An introduction to some of the mathematical foundations of computer science, particularly logic, automata, and computability theory. Develops skill in constructing and writing proofs, and demonstrates the applications of the aforementioned areas to problems of practical significance.

CS 105. Computer Systems

Prerequisites
CSCI070 HM

Credit Hours
3.0

Offered
Both semesters

An introduction to computer systems. In particular, the course investigates data representations, machine level representations of programs, processor architecture, program optimizations, the memory hierarchy, exceptional control flow (exceptions, interrupts, processes and Unix signals), performance measurement, caches and virtual memory, system-level I/O, networking, and basic concurrent programming. These concepts are supported by a series of hands-on lab assignments.

CS 111. Domain-Specific Languages

Prerequisites
CSCI070 HM

Credit Hours
3.0

This course explores how to design a new programming language. In particular, we’ll focus on “Domain-Specific Languages”—languages designed for people who want to use a computer to perform a specialized task (e.g., to compose music or query a database or make games). Through readings, discussions, and programming, we’ll investigate why and how you would create a domain-specific language. The course also features a project that asks you to propose, design, and implement your own domain-specific language.

CS 121. Software Development

Prerequisites
CSCI070 HM

Credit Hours
3.0

Offered
Both semesters

Introduction to the discipline concerned with the design and implementation of software systems. The course presents a historical perspective on software development practice and explores modern, agile techniques for eliciting software requirements, designing and imple­menting software architecture and modules, robust testing practices, and project management. Student teams design, develop, and test a substantial software project.

CS 124. Interaction Design

Prerequisites
CSCI042 HM or CSCI060 HM

Credit Hours
3.0

This course introduces students to issues in the design, implementation, and evalu­ation of human-computer interfaces, with emphasis on user-centered design and graphical interfaces. In this course, students learn skills that aid them in choosing the right user interaction technique and developing an interface that is well-suited to the people for whom it is designed.

CS 125. Computer Networks

Prerequisites
CSCI105 HM

Credit Hours
3.0

Principles and analysis techniques for internetworking. Analysis of network­ing models and protocols. Presentation of computer communication with emphasis on protocol architecture.

CS 131. Programming Languages

Prerequisites
CSCI070 HM and CSCI081 HM

Credit Hours
3.0

Offered
Fall and Spring

A thorough examination of issues and features in language design and implementation including language-provided data structuring and data-typing, modularity, scoping, inheritance, and concurrency. Compilation and run-time issues. Introduction to formal semantics.

CS 132. Compiler Design

Prerequisites
CSCI105 HM and CSCI131 HM

Credit Hours
3.0

The design and implementation of compilers. Topics include elegant theoretical results underlying compilation techniques, practical issues in efficient implementation of program­ming languages, and bit-level interactions with operating systems and computer architec­tures. Over the course of the semester, students build a working compiler.

CS 133. Database Systems

Prerequisites
CSCI070 HM; CSCI081 HM recommended

Credit Hours
3.0

Fundamental models of databases: entity-relationship, relational, object-oriented. Relational algebra and calculus, query languages. Data storage, caching, indexing, and sorting. Locking protocols and other issues in concurrent and distributed databases.

CS 134. Operating Systems: Design and Implementation

Prerequisites
CSCI105 HM

Credit Hours
3.0

Design and implementation of operating systems, including processes, memory management, synchronization, scheduling, protection, file systems, and I/O. These concepts are used to illustrate wider concepts in the design of other large software systems, including simplicity; efficiency; event-driven programming; abstraction design; client-server architec­ture; mechanism vs. policy; orthogonality; naming and binding; static vs. dynamic, space vs. time, and other trade-offs; optimization; caching; and managing large code bases. Group projects provide experience in working with and extending a real operating system.

CS 137. File Systems

Prerequisites
CSCI105 HM

Credit Hours
3.0

Computer storage and file systems. Characteristics of nonvolatile storage, including magnetic disks and solid-state memories. RAID storage. Data structures used in file systems. Performance, reliability, privacy, replication, and backup. A major portion of the course is devoted to readings selected from current research in the field.

CS 140. Algorithms

Joint Listings
Math168 HM

Prerequisites
((CSCI070 HM and CSCI081) or ((CSCI060 HM or CSCI042 HM) and MATH131 HM))

Credit Hours
3.0

Offered
Both semesters

Algorithm design, analysis, and correctness. Design techniques including divide-and-conquer and dynamic programming. Analysis techniques including solutions to recurrence relations and amortization. Correctness techniques including invariants and inductive proofs. Applications including sorting and searching, graph theoretic problems such as shortest path and network flow, and topics selected from arithmetic circuits, parallel algorithms, computational geometry, and oth­ers. An introduction to computational complexity, NP-completeness, and approximation algorithms. Proficiency with programming is expected as some assignments require algorithm implementation. (Crosslisted as MATH168 HM)

CS 142. Complexity Theory

Joint Listings
Math167 HM

Prerequisites
CSCI081 HM

Credit Hours
3.0

Brief review of computability theory through Rice’s Theorem and the Recursion Theorem followed by a rigorous treatment of complexity theory. The complexity classes P, NP, and the Cook-Levin Theorem. Approximability of NP-complete problems. The polynomial hierarchy, PSPACE-completeness, L and NL-completeness, #P-completeness. IP and Zero-knowledge proofs. Randomized and parallel complexity classes. The speedup, hierarchy, and gap theorems. (Crosslisted as MATH167 HM

CS 144. Scientific Computing

Joint Listings
Math164 HM

Prerequisites
MATH073 HM, MATH082 HM, and (CSCI060 HM or CSCI042 HM)

Credit Hours
3.0

Computational techniques applied to problems in the sciences and engineering. Modeling of physical problems, computer implementation, analysis of results; use of mathematical software; numerical methods chosen from: solutions of linear and nonlinear algebraic equations, solutions of ordinary and partial differential equations, finite elements, linear programming, optimization algorithms, and fast Fourier transforms. (Crosslisted as Math164 HM)

CS 145. Advanced Topics in Algorithms

Prerequisites
CSCI140 HM or MATH168 HM

Credit Hours
1.5

The objective of this course is to explore sophisticated algorithm design and analysis techniques that are generally not taught in a first algorithms course. The course addresses topics such as graph matching, competitive analysis of online algorithms, matroid theory, and approximation algorithms and schemes.

CS 151. Artificial Intelligence

Prerequisites
CSCI070 HM and (MATH062 HM or BIOL154 HM)

Credit Hours
3.0

This course presents a general introduction to the field of Artificial Intelligence. It examines the question: What does (will) it take for computers to perform human tasks? It presents a broad introduction to topics such as knowledge representation, search, learning and reasoning under uncertainty. For each topic, it examines real-world applications of core techniques to problems which may include game playing, text classification and visual pattern recognition.

CS 152. Neural Networks

Prerequisites
(CSCI060 HM or CSCI042 HM) and MATH073 HM and (MATH062 HM or BIOL154 HM)

Credit Hours
3.0

Modeling, simulation, and analysis of artificial neural networks and their relation to biological networks. Design and optimization of discrete and continuous neural networks. Back propagation and other gradient descent methods. Hopfield and Boltzmann networks. Unsupervised learning. Self-organizing feature maps. Applications chosen from function approximation, signal processing, control, computer graphics, pattern recognition, time-series analysis. Relationship to fuzzy logic, genetic algorithms, and artificial life.

CS 153. Computer Vision

Prerequisites
CSCI060 HM or CSCI042

Credit Hours
3.0

Computational algorithms for visual perception. Students will develop applications that acquire, process and interpret still images and image streams. The course will cover representations of color, shading, texture and shape along with stereo and motion analysis, object recognition and approaches for three-dimensional representation. Applications include robotics, human perception and the use of large image databases.

CS 155. Computer Graphics

Prerequisites
CSCI070 HM, MATH073 HM, and (MATH062 HM or BIOL154 HM)

Credit Hours
3.0

This course is an introduction to the major concepts in modern computer graphics. Students will become familiar with the technical challenges posed by the capture, display, and generation of digital images. Important concepts such as the role of specialized hardware, trade-offs in physical realism and rendering time, and the critical reading and analysis of graphics literature will be introduced.

CS 158. Machine Learning

Prerequisites
CSCI070 HM, MATH073 HM, and (MATH062 HM or BIOL154 HM); CSCI151 HM recommended

Credit Hours
3.0

Machine learning is concerned with the study and development of systems that learn patterns in data. This course introduces the most common problems in the field and the techniques used to tackle these problems, with a focus on supervised and unsupervised learning. Concepts include mathematical foundations and algorithmic approaches.

CS 159. Natural Language Processing

Prerequisites
CSCI081 HM and (MATH062 HM or BIOL154 HM)

Credit Hours
3.0

An introduction to the fundamental concepts and ideas in natural language processing, sometimes called computational linguistics. The goals of the field range from text translation and understanding to enabling humans to converse with robots. We will study language processing starting from the word level to syntactic structure to the semantic meaning of text. Approaches include statistical as well as symbolic methods using logic and the lambda calculus. Students will build and modify systems and will use large existing corpora for validating their systems.

CS 181. Computer Science Seminar

Prerequisites
Permission of instructor

Credit Hours
3.0

Offered
Fall and Spring

Advanced topics of current interest in computer science.

CS 183–184. Computer Science Clinic I, II

Prerequisites
CSCI121 HM, CSCI183 HM, and Senior standing; or permission of the Clinic Director

Credit Hours
3.0

Offered
183 in Fall, 184 in Spring

The Clinic Program brings together teams of students to work on a research problem sponsored by business, industry, or government. Teams work closely with a faculty advisor and a liaison provided by the sponsoring organization to solve complex real-world problems. Students are expected to present their work orally and to produce a final report conforming to professional publication standards.

CSCI183 HM and CSCI185 HM must be taken consecutively to count toward the CS major.

CS 186. Computer Science Research and Independent Study

Prerequisites
Permission of instructor

Credit Hours
0.5–3.0

Offered
Both semesters

A research or development project under computer science faculty supervision. No more than 3 units can count toward major elective credit.

CS 189. Programming Practicum

Prerequisites
CSCI005 HM or CSCI005GR HM or CSCI042 HM

Credit Hours
1.0

Offered
Both semesters

This course is a weekly programming seminar, emphasizing efficient recognition of computational problems and their difficulty, developing and implementing algorithms to solve them, and the testing of those implementations. Attention is given to the effective use of programming tools and available libraries, as well as to the dynamics of team problem-solving. No more than 3 credits can count toward the major elective requirement.

Repeatable: May be taken for major elective credit up to three times

CS 195. Computer Science Colloquium

Prerequisites
Junior or Senior only

Credit Hours
0.5

Offered
Fall and Spring

Oral presentations and discussions of selected topics, including recent developments in computer science. Participants include computer science majors, Clinic participants, faculty members, and visiting speakers. No more than 2.0 credits can be earned for departmental seminars/col­loquia. All majors welcome.