Cognitive Science (BS) Computer Science

Study of biological processes at the suborganismal level including cell chemistry, metabolism, reproduction, genetics, and complex tissue physiology. Laboratory and discussion sessions stress problem solving and experimental design.

Prerequisites: none

Goal Areas: GE-03

Limits, continuity, the derivative and applications, transcendental functions, L'Hopital's Rule, and development of the Riemann integral.

Prerequisites: Satisfy Placement Table in this section, MATH 115 or both MATH 112 and MATH 113 with “C” (2.0) or better.

Goal Areas: GE-04

This course is an introduction to organic chemistry and biological chemistry. The laboratory will reinforce lecture.

Prerequisites: CHEM 106 or high school chemistry 

Goal Areas: GE-02, GE-03

Introduction to the basic principles of chemistry including atomic and molecular structure, bonding, chemical reactions, stoichiometry, thermodynamics and states of matter. Laboratory will reinforce lecture concepts. Prereq: C or higher in MATH 112 or the equivalent; high school chemistry or C or higher in CHEM 104

Prerequisites: “C” (2.0) or higher in MATH 112 or the equivalent; high school chemistry or “C” (2.0) or higher in CHEM 104.

Goal Areas: GE-02, GE-03

Students will learn programming skills in object-oriented C++. Students will design algorithms and learn how to write, compile, run and debug programs that include selection and repetition structures, functions, and arrays. Study skills and professional development will be addressed.Fall, Spring

Prerequisites: MATH 112 (College Algebra)

This course introduces a multidisciplinary approach to the scientific study of cognition. Contributions from the fields of biology, computer science, neuroscience, philosophy, and psychology are emphasized. Topics include the mind-body problem, perception, memory, linguistics, problem solving, artificial intelligence, and robotics. This course is a prerequisite for the cognitive science major. For the psychology major, it serves as unrestricted elective credit; it does not satisfy the cognitive restricted elective requirement.

Prerequisites: none

Goal Areas: GE-05

Introduction to statistical analysis as applied to the health sciences. Examines concepts and methods of statistical procedures applied to health problems and issues.

Prerequisites: MATH 110, STAT 154, Or any other mathematics course higher than MATH 110.

This course emphasizes understanding the conceptual basis of common statistical procedures and applying those procedures to the problems of organizing information and making inferences from data. Topics include: summarizing data, the logic of inference, estimation, analysis of variance, and correlation.

Prerequisites: Complete one course: MATH 112, MATH 113, MATH 115, MATH 121, MATH 130, or STAT 154

An introduction to statistical concepts and methods that is applicable to all disciplines. Topics include descriptive measures of data, probability and probability distributions, statistical inference, tests of hypotheses, confidence intervals, correlation, linear regression, and analysis of variance. The use of statistical software will be emphasized. Prereq: ACT Math sub-score of 19 or higher, successful completion of MATH 098 or appropriate placement scores (see Placement Information under Statistics) Fall, Spring, Summer GE-4

Prerequisites: Satisfy Placement Table in this section, or MATH 098 with grade of P. 

Goal Areas: GE-02, GE-04

A calculus based introduction to probability and statistics. Topics include probability, random variables, probability distributions (discrete and continuous), joint probability distributions (discrete and continuous), statistical inference (both estimation and hypothesis testing), confidence intervals for distribution of parameters and their functions, sample size determinations, analysis of variance, regression, and correlation. This course meets the needs of the practitioner and the person who plans further study in statistics. Same as MATH 354. Prereq: MATH 122 with C or better or consent Fall, Spring, Summer

Prerequisites: MATH 122 with C or better or consent 

Systems approach to the structure of the human body. The course is designed for students majoring in biology or health related programs. Lab included.

Prerequisites: none

Basic anatomy and physiology of the nervous system. The course is designed for students majoring in biology, psychology or health related programs.

Prerequisites: BIOL 220 

Principles of functions of human cells, organs, and systems with an emphasis on organ/system interactions. This course is designed for students majoring in biology, chemistry, or related sciences, and medically-related areas. Includes a laboratory with a research and medical emphasis.

Prerequisites: BIOL 220, CHEM 104 or CHEM 106 or CHEM 111 or CHEM 201

Continues the exploration of introductory Computer Science begun in CS 110. Focus is on developing basic knowledge of algorithms, programming skills and problem solving techniques. Topics include recursion, sorting, linked lists, stacks and queues.Fall, Spring

Prerequisites: CS 110 or EE 107. MATH 113 or MATH 115 or MATH 121

Fundamentals of data mining and knowledge discovery. Methods include decision tree algorithms, association rule generators, neural networks, and web-based mining. Rule-based systems and intelligent agents are introduced. Students learn how to apply data-mining tools to real-world problems.

Prerequisites: CS 110

This course considers historical and contemporary analyses of the mind in relation to the body and the connection of the mind-body problem to other issues concerning both religion and science.

Prerequisites: none

Goal Areas: GE-06

This course examines the conceptual and philosophical complexities of efforts to understand the mind in science. Topics include the difference and similarities between humans and other animals, the nature of psychological explanation, and reductive strategies for explaining consciousness, intentionality and language. Fall

Prerequisites: none

An introduction to the major components of research methodology in psychology. This is a writing intensive course and involves the processing, interpretation, and exposition of behavioral data.

Prerequisites: Must have a minimum total cumulative GPA of 2.70 or instructor permission to enroll; PSYC 201

This course will introduce students to the relationship between the structure and function of the nervous system to the underlying biological processes of behavior.

Prerequisites: PSYC 201

Explores the scientific study of human cognition and provides students with broad coverage of the mental processes used to acquire, process, and retain knowledge. Students will examine basic concepts and research findings in topics of human cognition such as perception, attention, memory, reading, and problem solving. Concepts in Cognitive Psychology will be related to everyday behaviors and experiences.

Prerequisites: either Psy 101 OR Psy 206, not both

Basic introductory concepts and a history of the field of Artificial Intelligence (AI) are covered. Emphasis is placed on the knowledge representation and reasoning strategies used for AI problem solving. Solutions are found using the LISP programming language.Fall (ALT)

Prerequisites: CS 230 or CS 305

This course discusses concepts and techniques for design, development and evaluation of user interfaces. Students will learn the principles of interaction design, interaction styles, user-centered design, usability evaluation, input/output devices, design and analysis of controlled experiments and principles of perception and cognition used in building efficient and effective interfaces. Group project work.

Prerequisites: IT 380 or CS 230; STAT 154 or PSYC 201 and MATH 121

Study of the elements of first order symbolic logic, i.e., the propositional calculus and the predicate calculus, and its applications to ordinary language and mathematics.

Prerequisites: none

Goal Areas: GE-02, GE-04

Theories of meaning, speech acts and semantics, relation of language to the world.

Prerequisites: none

The nature of consciousness, mind and body relations, freedom of action.

Prerequisites: none

Cognitive and epistemic issues surrounding sensory perception, including the nature of perception, its immediate objects, and its ability to deliver knowledge of the world.

Prerequisites: none

Philosophical issues concerning the mental lives of non-human animals, with emphasis on consciousness, rationality, language, and implications for non-human animal ethics.

Prerequisites: none

Nature of explanations, causality, theoretical entities, and selected problems.

Prerequisites: none

This course examines conceptual and philosophical issues in biology, the nature and scope of biological explanation and conflicts between evolutionary and religious explanations for the origin of life.

Prerequisites: none

Study of the core algorithm design and analysis techniques of computer science and the data structures which support them with attention to the applicability to specific problem types and comparison metrics.

Prerequisites: CS 111, MATH 121

Advanced study and research required. Topic of the senior thesis determined jointly by the student and the faculty advisor.Fall, Spring Prereq: Senior standing and consent

Prerequisites: Senior standing and consent

An introduction to methods, algorithms, and tools of cryptography. We will study the algorithmic and mathematical aspects of cryptographic methods and protocols. We will experiment with how they can be used to solve particular data and communication security problems. Prerequisite: CS 305 or permission of instructor.

Prerequisites: CS 305 or permission of instructor.

This course provides an introduction to the theory and practice of neural computation. The goal is to familiarize students with the major models, techniques, and problems of neural network computation and to provide hands-on experience using these things. Topics include neural network models, supervised and unsupervised learning, associative memory models, and data representation.

Prerequisites: CS 230

Basic introductory concepts and a history of the field of Artificial Intelligence (AI) are covered. Emphasis is placed on the knowledge representation and reasoning strategies used for AI problem solving. Solutions are found using the LISP programming language.Fall (ALT)

Prerequisites: CS 230 or CS 305

This course discusses concepts and techniques for design, development and evaluation of user interfaces. Students will learn the principles of interaction design, interaction styles, user-centered design, usability evaluation, input/output devices, design and analysis of controlled experiments and principles of perception and cognition used in building efficient and effective interfaces. Group project work.

Prerequisites: IT 380 or CS 230; STAT 154 or PSYC 201 and MATH 121