Computer Science

measurements, analyze them statistically, and interpret their significance. Prerequisite: CHEM 202 and CHEM 301. Offered each spring. 304 Instrumental Analysis Principles of the design and use of modern electronic instrumentation in the chemistry laboratory with emphasis on spectral, electroanalytical and chromatographic instrumentation. Prerequisite: CHEM 302. Offered in alternate fall semesters. 311, 312 Organic Chemistry (1.25) (311 - PSL) Fundamentals of aliphatic and aromatic chemistry including mechanisms, syntheses, stereochemistry, and spectroscopy. Prerequisites: CHEM 202 (grade of C- or better); 311(grade of C- or better) for 312. Both offered each semester. 317 Survey of Biochemistry An introduction to the fundamental principles of biochemistry and the application of chemical principles to biological problems. Topics include the structure and function of proteins, nucleic acids, carbohydrates, lipids, as well as the major catabolic and biosynthetic pathways. Prerequisites: BIOL 102 or 108, and CHEM 312 (grade of C- or better), or the consent of instructor. Offered each spring. 321 Physical Chemistry I: Thermodynamics (1.25) Classical thermodynamics and its applications in chemistry. Prerequisites: CHEM 202, PHYS 101 or 105, MATH 176. Offered each fall. 322 Physical Chemistry II: Kinetics Kinetic molecular theory, mass transport, experimental and theoretical chemical kinetics. Prerequisites: CHEM 202, PHYS 102 or 106, MATH 177. Offered each spring. 323 Quantum Mechanics (Cross-listed with PHYS 407) Wave mechanics, the Schroedinger equation, operator formalism, the harmonic oscillator, the hydrogen atom, angular momentum, spin, scattering theory, chemical bonding, electromagnetic interaction. Prerequisite: PHYS 304. Offered in alternate years. 324 Statistical Physics (Cross-listed with PHYS 408) Introduces central principles underlying thermodynamic properties found in large collections of atoms and molecules (i.e. systems with many degrees of freedom). A core pillar of the major, Statistical Physics is recommended for any student considering graduate school in Physics, and for Chemistry Majors, reinforcing key elements of Physical Chemistry. Prerequisite: PHYS 207 or CHEM 332. Offered in alternate years. 332 Inorganic Chemistry An introduction to the fundamentals of inorganic chemistry including atomic structure; metallic, ionic, and covalent substances; acids and bases; coordination compounds; and descriptive chemistry of the elements. Students will use electronic structure, modern bonding theories, and models (tangible, virtual, and theoretical) to systematically understand the physical and chemical properties of inorganic substances. Prerequisite: CHEM 202. Offered each spring. 340 Introduction to Food Biochemistry: Hawaii (LSI, US) This course focuses on the fundamental biology and chemistry of food preparation and metabolism as well as the agricultural production of food processing, and food manufacture. Students will meet with local farmers, molecular biologists, horticulturists, and USDA scientists to examine the science behind modern food production techniques in Hawaii. Prerequisites: BIOL 102 or 108 and CHEM 202. Offered in alternate years, May. 380 Advanced Inorganic Synthesis and Analysis (1) (W) Individualized projects which emphasize techniques of advanced inorganic synthesis and instrumental analysis. Prerequisites: CHEM 301 and 321. Offered each spring. 397 Internship in Chemistry Internships in scientific research centers or industrial laboratories. Prerequisites: sophomore status and consent of department chair. This course does not meet major requirements. Internship offered for 0.5 or 1.0 course units. Offered occasionally.

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Chemistry and Biochemistry

413 Advanced Organic Chemistry A detailed examination of selected classical and modern topics within organic chemistry. Topics may include pericyclic reactions, spectroscopic methods of structure determination, physical-organic chemistry, synthetic trans-formations and strategy, and bio-organic/medicinal chemistry. Prerequisite: C- or better in CHEM 312. Offered annually. 414 Biochemistry I (1)(1.25) The fundamentals of biochemistry, including an exploration of biomolecules and an introduction to experimental techniques. An emphasis is placed on understanding the structure and function of proteins, enzyme kinetics and regulation, nucleic acid chemistry, and bioenergetics. Offered for 1.0 unit without lab or for 1.25 units with optional four-hour laboratory. Prerequisite: CHEM 312 (grade of C- or better) or consent of instructor. Offered each fall. 415 Biochemistry II (W) A continuation of Chemistry 414. Topics include the major catabolic and anabolic pathways, the integration and regulation of these pathways, cell signaling and biochemical genetics. The majority of the readings for this course will come from the current primary literature. Prerequisite: CHEM 414. Offered each spring. 432 Advanced Inorganic Chemistry A detailed examination of advanced topics in inorganic chemistry. Topics will include the quantum atom and electronic states; the application of molecular symmetry and group theory to spectroscopy and X-ray crystallography; the mechanisms of inorganic reactions; bioinorganic chemistry; and catalysis. Prerequisites: CHEM 332 or consent of instructor. Offered occasionally. 470 Special Topics in Chemistry (.5) (1) Designed to offer topics not normally covered by the chemistry curriculum. Topics offered for 1.0 units may be used as electives toward the chemistry major or minor and two 0.5 unit topics may together serve as an elective. May be repeated for credit if subject matter is different. Prerequisite: varies by topic. Offered occasionally. 495 Directed Study (.5) (1) Individualized directed readings on a topic of interest to the student which is not normally a part of the curriculum. The work may include a laboratory component. It may also include the requirement for the preparation of a significant paper which brings together the results of the study. Prerequisite: Consent of instructor. Offered each semester. 499 Research/Thesis (.5) (1) (W) Directed or independent study of a specialized topic which may include laboratory research. May be repeated for a maximum of two course units. Prerequisites: Junior standing, four previous course units in chemistry, and consent of instructor. Offered each semester.

COMPUTER SCIENCE

Liffiton, Law, Shallue, Sheese

Computer science is the study of what computers can and cannot do. Central to that study is the concept of the algorithm, a set of directions for solving a problem or accomplishing a task. Computer science studies algorithms in terms of their implementation in hardware and software, their analysis, and their applications. The curriculum in computer science provides students with an understanding of the fundamental principles of computing and of the capabilities, limitations, and applications of algorithmic problem solving. It provides students with the central skills of the discipline: fluency in multiple approaches to programming and problem solving, the ability to use levels of abstraction to manage complexity, and preparation to adapt to technological changes in the field. It provides students with the ability to convey technical information in written and oral communication to all audiences, experts and non-experts alike.

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Computer Science

Major Sequence in Computer Science:

A minimum of twelve courses to include: 1) CS 125, 126 or 127; students who are placed directly into CS 128 need to take an additional course that counts towards the major to replace this course. 2) CS 128, 253, 256, 354, and 355 3) Four additional upper-level courses in computer science 4) MATH 135 and 136

Minor Sequence in Computer Science:

A minimum of six courses to include: 1) CS 125, 126 or 127; students who are placed directly into CS 128 need to take an additional course that counts towards the minor to replace this course. 2) CS 128 3) Three additional courses, one at the 200-level or above and two at the 300-level or above in computer science 4) MATH 135 or 136 Only one of the courses CS 125, 126 and 127 will count towards the major or minor in computer science. Students in the major or minor with previous experience may opt to skip CS 125, 126, and 127, instead starting in CS 128. This requires approval of the department chair, and it requires taking an additional course that counts toward the computer science major or minor to take the place of the skipped course.

At most, one of CS 498 and CS 499 may count toward completion of the major degree requirements; neither may count for the minor degree requirements.

125 Introduction to Computer and Data Sciences (FR) (Cross-listed with DASC

125) Computer Science studies how to solve problems using computers. Data science focuses on acquiring, cleaning, and exploring data, via visualization and statistical analysis, to aid decision making. This course introduces programming, the fundamental skill of computer science, using data science examples and applications in the Python programming language. May not be taken for credit after successfully completing CS 126 or CS 127. No prerequisites. Offered each term. 126 Introduction to Computer Science Using the Web (FR) Introduction to object based programming using JavaScript to create dynamic web pages. Includes a brief introduction to HTML and CSS, with emphasis on the division of structure and presentation. Topics: internet architecture and history, selection, iteration, functions, operators, objects, methods, properties, arrays, strings, event handlers, and form processing. May not be taken for credit after successfully completing CS 125 or CS 127. No prerequisites. Offered annually. 127 Computer Science I (FR) Computer science studies how to solve problems using computers. This course introduces computer science as a field of study and programming as a core component thereof. Covers programming concepts and techniques; variables, data types, lists, loops, conditionals, functions, objects, classes, testing, debugging, and program design. Teaches the Python programming language. May not be taken for credit after successfully completing CS 125 or CS 126. No prerequisites. Offered each term. 128 Computer Science II Introduction to data structures and algorithmic problem solving. Encapsulation and information hiding, recursion, algorithm techniques, and time complexity. Advanced object oriented programming with inheritance, static and dynamic memory allocation. Linked lists, stacks, queues, and sequential and binary search. Teaches the C++ programming language and UNIX command line fundamentals. Prerequisite: CS 125/DASC 125, CS 126, or CS 127. Offered each term.

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Computer Science

135 Applications of Sets, Logic, and Recursion (FR) (Cross-listed as MATH 135)

Introduction to functional programming and discrete mathematics. Sets, functions, and relations. Basic logic, including formal derivations in propositional and predicate logic. Recursion and mathematical induction. Programming material: Data types and structures, list-processing, functional and recursive programming. No prerequisite. Offered each spring. 136 Computational Discrete Mathematics (Cross-listed as MATH 136) Additional concepts in discrete mathematics. Recurrence relations, counting, and combinatorics. Discrete probability. Algorithmic graph theory. Programming with advanced data structures. No prerequisite. Offered each fall.

222 Ethics, Values and Issues in Cybertechnology (AV, W) (Cross-listed with

PHIL 222) An overview of the ethical issues which shape modern technology, including such topics as free expression and content control, intellectual property, privacy and information access, crime and security, and concepts, methodology, and codes of cyberethics. Theory and actual cases will be analyzed in readings, discussion, and written work. Will not count toward the major or minor. No prerequisites. Offered annually. 253 Software Development (W) Explores the application of computer science through the software development process. Focuses on software engineering and the production of complete programs, from planning and user interface design through coding, testing, development, and maintenance. Additionally, the course covers several aspects of technical writing, encompassing documentation, specifications, and communication with clients. Prerequisite: CS 128 with a C- or above. Offered each fall. 256 Computer Organization and Architecture Introduction to computer organization and system architecture. Topics: Boolean algebra, combinational and sequential logic design, fundamental structure of major computer hardware systems (CPU/ALU, memory, cache, registers, I/O), instruction sets, computer arithmetic, pipelining, and memory hierarchy. A two-hour weekly hardware lab is required. Prerequisites: CS 128 with a C- or above. Offered each spring. 314 Database Systems Introduction to the relational and semi-structured data base models. Theoretical concepts include relational algebra and calculus, logical and physical database design, normalization, database security and integrity, data definition and data manipulation languages. Programming topics: database creation, modification, and querying using XQuery, MySQL and PHP. Prerequisite: CS 128 with a C- or above and MATH 135. Offered in alternate years. 330 Computer Networking Introduction to computer networking, from single, physical links to the structure of the global internet. Focuses on the internet and related technologies, its nuts and bolts, and the principles that govern how and why it works. Several advanced topics are covered, often drawn from the rapidly advancing forefront of network applications. Prerequisite: CS 128 with a C- or above and CS/MATH 136. Offered in alternate years. 338 Artificial Intelligence Artificial intelligence is, broadly, the study of computational solutions to difficult real-world problems – problems whose solutions might be considered to involve “intelligence”. Applications range from self-driving cars to intelligent personal agents to challenging routing/scheduling problems. Topics include Bayesian inference, constraint satisfaction, game playing, logic, machine learning, Markov decision processes, and heuristic search. Prerequisites: CS 128 with a C- or above, MATH/CS 135, and MATH/CS 136. Offered in alternate years. 354 Algorithm Design and Analysis Explores efficient programming through the study of algorithms and data structures. Algorithm complexity analysis. Common patterns and trade-offs; e.g., recursion, divide and conquer, greedy algorithms, parallelization, etc. Advanced data structures and abstract data models; e.g., linked structures, array-based

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Computer Science