This course will focus on the epidemiology, history, methods, and ancillary laboratory tools used in the study and control of healthcare associated adverse events, including discussions of key concepts and theory, basic types of epidemiological investigations and study designs, and distinctive problems associated with specific risk factors. Adverse events will be discussed as components of patient safety and the quality of care.
Prevention of water-related diseases by appropirate supply and sanitation practices with designs applicable to small systems and rural areas of developing nations.
This course offers a structural exposure of students to the varieties of basic and clinical science research and current issues in healthcare policy under discussion at the University Medical Center. Following weekly attendance at research seminars and clinical rounds, students will present their observations in follow-up discussion groups. May be repeated to a maximum of three credits.
Characteristics of a procedure-oriented language; high-level description of computer structure and information representation schemes; introduction to algorithm development and design. Emphasis will be placed on the programming tools used in software engineering. Tools suitable for programming development on microcomputers will be emphasized. Not open to student who have received credit for CS 121 or CS 221.
An introduction to computer-assisted problem solving for civil engineering students using a microcomputer based procedure-oriented language; a description of internal structure and representation of information; an introduction to algorithms. Emphasis will be placed on the solution of characteristic problems arising in civil engineering.
Study of computer science techniques and tools that support computational sciences and engineering. Emphasis on visualization, performance evaluation, parallel computing, and distributed computing.
This course covers the fundamental concepts involved in understanding and engineering a closed- loop, sensing, reasoning, and actuating agent. Biological models of sensing and actuation will be discussed and related to modern artificial counterparts. The course consists of three major topic areas: vision, brain, and robotics.
The course covers fundamentals of propositional and predicate logic, and their uses in declarative programming to model and solve computational problems. Topics include propositional satisfiability, satisfiability testing techniques such as the DPLL algorithm, automated reasoning techniques for predicate logic such as resolution with unification and logic programming.
The course examines the requirements phase of the Sys- tems Engineering and Software Engineering lifecycles in detail. Topics include: requirements elicitation, requirements specification, and requirements analysis. Verification and validation techniques are emphasized throughout the course. Students work in small groups to research and present a related topic.
The course will present advanced computational science techniques needed to support large scale engineering and scientific computations. Emphasis on iterative methods for solving large sparse linear systems and parallel implementations of iterative techniques.
