CS Course Descriptions

  • CSCI005 HM

    Credits: 3

    Instructors: Dodds, Kuenning, Medero, Schofield

    Offered: Fall

    Description: 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.

  • CSCI005GR HM

    Credits: 3

    Instructors: Wu, Bush (Biology)

    Offered: Fall

    Description: 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.

  • CSCI035 HM

    Credits: 3

    Instructor: Dodds

    Description: 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.

    Prerequisites: CSCI005 HM or CSCI005GR HM 

  • CSCI042 HM

    Credits: 3

    Instructor: Stone and Wiedermann

    Offered: Fall

    Description: 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.

    Prerequisites: Permission of instructor

  • CSCI060 HM

    Credits: 3

    Instructors: Boerkoel, Breeden, Dodds, Stone, Trushkowsky, Wu

    Offered: Fall and spring

    Description: 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.

    Prerequisites: CSCI005 HM or CSCI005GR HM 

  • CSCI070 HM

    Credits: 3

    Instructors: Bang, Breeden, Medero, O'Neill, Stone, Talvitie, Trushkowsky, Wiedermann

    Offered: Fall and spring

    Description: 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.

    Prerequisites: (CSCI060 HM or CSCI042 HM), and at least one mathematics course at the level of calculus or higher; MATH055 HM recommended

  • CSCI081 HM

    Credits: 3

    Instructors: Bang, Monta​ñez, Stone

    Offered: Fall and spring

    Description: 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.

    Prerequisites: MATH055 HM and (CSCI060 HM or CSCI042 HM)

  • CSCI105 HM

    Credits: 3

    Instructors: Kuenning, Stone, Sweedyk, Trushkowsky

    Offered: Fall and spring

    Description: 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.

    Prerequisites: CSCI070 HM 

  • CSCI111 HM

    Credits: 3

    Instructor: Wiedermann

    Description: 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.

    Prerequisites: CSCI070 HM 

  • CSCI121 HM

    Credits: 3

    Instructors: Sweedyk, Wu

    Offered: Fall and spring

    Description: 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.

    Prerequisites: CSCI070 HM 

  • CSCI124 HM

    Credits: 3

    Instructor: Boerkoel

    Description: 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.

    Prerequisites: CSCI042 HM or CSCI060 HM 

  • CSCI125 HM

    Credits: 3

    Instructors: Kuenning, Stone

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

    Prerequisites: CSCI105 HM 

  • CSCI131 HM

    Credits: 3

    Instructors: Bang, O'Neill, Stone, Wiedermann

    Offered: Fall and spring

    Description: 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.

    Prerequisites: CSCI070 HM and CSCI081 HM 

  • CSCI132 HM

    Credits: 3

    Instructors: Stone, Wiedermann

    Description: 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.

    Prerequisites: CSCI105 HM and CSCI131 HM 

  • CSCI133 HM

    Credits: 3

    Instructor: Trushkowsky

    Description: 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.

    Prerequisites: CSCI070 HMCSCI081 HM recommended

  • CSCI134 HM

    Credits: 3

    Instructors: Kuenning, O'Neill, Stone, Staff

    Description: 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.

    Prerequisites: CSCI105 HM 

  • CSCI137 HM

    Credits: 3

    Instructors: Kuenning, Staff

    Description: 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.

    Prerequisites: CSCI105 HM 

  • CSCI140 HM

    Credits: 3

    Instructors: Boerkoel, Monta​ñez, Schofield, Stone

    Offered: Fall and spring

    Description: 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.

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

  • CSCI142 HM

    Credits: 3

    Instructor: Staff

    Description: 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.

    Prerequisites: CSCI081 HM 

  • CSCI144 HM

    Credits: 3

    Instructors: Bernoff (Mathematics), de Pillis (Mathematics), Yong (Mathematics)

    Description: 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.

    Prerequisites: MATH073 HMMATH082 HM, and (CSCI060 HM or CSCI042 HM

  • CSCI145 HM

    Credits: 1.5

    Instructor: Staff

    Description: 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.

    Prerequisites: CSCI140 HM or MATH168 HM 

  • CSCI151 HM

    Credits: 3

    Instructors: Boerkoel, Talvitie, Wu

    Description: 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.

    Prerequisites: CSCI070 HM and (MATH062 HM or BIOL154 HM

  • CSCI152 HM

    Credits: 3

    Instructor: Sweedyk

    Description: 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.

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

  • CSCI153 HM

    Credits: 3

    Instructor: Staff

    Description: 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.

    Prerequisites: CSCI060 HM or CSCI042 HM 

  • CSCI155 HM

    Credits: 3

    Instructors: Breeden, Sweedyk

    Description: 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.

    Prerequisites: CSCI070 HMMATH073 HM, and (MATH062 HM or BIOL154 HM)

  • CSCI158 HM

    Credits: 3

    Instructor: Wu

    Description: 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.

    Prerequisites: CSCI070 HMMATH073 HM, and (MATH062 HM or BIOL154 HM); CSCI151 HM recommended

  • CSCI159 HM

    Credits: 3

    Instructors: Medero, Schofield

    Description: 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 structured and statistical methods, as well as exploration of current natural language research. Students will build and modify systems and will use large existing corpora for validating their systems.

    Prerequisites: CSCI081 HM and (MATH062 HM or BIOL154 HM)

  • CSCI181 HM

    Credit: 1-3

    Instructor: Staff

    Offered: Fall and spring

    Description: Advanced topics of current interest in computer science.

    Prerequisites: Permission of instructor

  • CSCI183 HM

    Credits: 3

    Instructor: Staff

    Offered: Fall

    Description: 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 CSCI184 HM must be taken consecutively to count toward the major.

    Prerequisites: CSCI121 HM and senior standing; or permission of the Computer Science Clinic director

  • CSCI184 HM

    Credits: 3

    Instructor: Staff

    Offered: Spring

    Description: 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 CSCI184  HM must be taken consecutively to count toward the major.

    Prerequisites: CSCI121 HMCSCI183 HM, and senior standing; or permission of the Computer Science Clinic director

  • CSCI186 HM

    Credit: 0.5-3

    Instructor: Staff

    Offered: Fall and spring

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

    Prerequisites: Permission of instructor

  • CSCI189 HM

    Credit: 1

    Instructors: Dodds, Stone, Sweedyk

    Offered: Fall and spring

    Description: 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.

    Prerequisites: CSCI005 HM or CSCI005GR HM or CSCI042 HM 

  • CSCI195 HM

    Credit: 0.5

    Instructor: Staff

    Offered: Fall and spring

    Description: 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.

    Prerequisites: Juniors and seniors only

  • CSMT181 HM

    Credits: 1.5-3

    Instructor: Staff

    Description: A course devoted to exploring topics of current interest. Topics announced prior to registration.

  • CSMT183 HM

    Credits: 3

    Instructor: Staff

    Offered: Fall

    Description: Team project in joint computer science and mathematics, with corporate affiliation. CSMT183 HM and CSMT184 HM must be taken consecutively to count toward the major.

    Prerequisites: Senior standing as a Joint CS/Math major, or permission of the Computer Science or Mathematics Clinic director.

  • CSMT184 HM

    Credits: 3

    Instructor: Staff.

    Offered: Spring

    Description: Team project in joint computer science and mathematics, with corporate affiliation. CSMT183 HM and CSMT184  HM must be taken consecutively to count toward the major.

    Prerequisites: CSMT183 HM 

  • MCBI117 HM

    Credits: 3

    Instructor: Donaldson-Matasci (Biology)

    Description: An introduction to game theory, a branch of mathematics that studies strategic interactions between individuals, with applications in fields such as biology, economics and political science. The course will introduce classical game theory, representations of games and Nash equilibria. The second part of the course will focus on evolutionary game theory, equilibrium concepts, and the evolution of cooperation.

    Prerequisites: Permission of instructor

  • MCBI118A HM

    Credits: 1.5

    Instructors: Adolph (Biology), de Pillis (Mathematics), Donaldson-Matasci (Biology)

    Offered: Spring

    Description: An introduction to the field of mathematical biology. Continuous and discrete mathematical models of biological processes and their analytical and computational solutions. Examples may include models in epidemiology, ecology, cancer biology, systems biology, molecular evolution, and phylogenetics.

    Prerequisites: MATH073 HMMATH082 HM, and BIOL046 HM 

  • MCBI118B HM

    Credits: 1.5

    Instructors: Bush (Biology), Donaldson-Matasci (Biology), Wu (Computer Science)

    Offered: Spring

    Description: An introduction to the field of computational biology. Algorithms for phylogenetic inference and computational methods for solving problems in molecular evolution and population genetics.

    Prerequisites: CSCI005 HM and BIOL046 HM 

  • MCBI199 HM

    Credit: 0.5

    Instructor: Staff

    Offered: Fall and spring

    Description: Students registered for joint colloquium must attend a fixed number of colloquium talks during the semester in any field(s) related to their interests. The talks may be at any members of The Claremont Colleges or a nearby university and may be in any of a wide array of fields including biology, mathematics, computer science and other science and engineering disciplines including bioengineering, cognitive science, neuroscience, biophysics, and linguistics. Students enrolled in the joint colloquium are required to submit a short synopsis of each talk that they attend. No more than 2.0 credits can be earned for departmental seminars/col­loquia.