This course provides an introduction to laboratory techniques in biomedical engineering. Laboratory exercises and demonstrations will explore topics, such as data acquisition, whole body monitoring, cell culture technique, microscopy, and material property characterization of biological materials. Students will learn proper handling of laboratory chemicals, operate common analytical instruments, describe the theory and applications of various analytical instruments, and practice laboratory safety.

The natural relationships between the atmosphere, hydrosphere, biosphere, and lithosphere; human impact on the natural environment. Global environmental issues: global warming, sea-level rise, and ozone depletion in the stratosphere. Global changes of the past also studied to give perspective to forecasted changes. Includes writing exercises. (Gen.Ed. PS)

The natural processes of the ocean, including earthquakes and volcanoes, the hydrologic cycle and weather, ocean circulation and the global energy balance, the carbon cycle and productivity, biodi-versity and marine food webs, coastal dynamics. Also, global warming, sea-level rise, environmental degradation and the ocean system response to human activity and global change. Interactive class sessions, with considerable participation by students in problem solving, discussions, and demonstrations. Exams and grades based on teamwork as well as on individual performance.

Nature and origin of the earth; volcanism; minerals and rocks; earthquakes; plate tectonics; mountain belts; geologic time scales; wave, river, glacial, and wind action in modification of landscape and atmosphere; the asteroid impact hypotheses; genesis of non-renewable resources, geologic basis for environmental decision making. Field excursions. (Gen.Ed. PS)

In this course, students will learn the fundamentals behind large-scale systems in the context of data science. We will cover the issues involved in scaling up (to many processors) and out (to many nodes) parallelism in order to perform fast analyses on large datasets. These include locality and data representation, concurrency, distributed databases and systems, performance analysis and understanding. We will explore the details of existing and emerging data science platforms, including MapReduce-Hadoop, Spark, and more.

In this course, students will learn the fundamentals behind large-scale systems in the context of data science. We will cover the issues involved in scaling up (to many processors) and out (to many nodes) parallelism in order to perform fast analyses on large datasets. These include locality and data representation, concurrency, distributed databases and systems, performance analysis and understanding. We will explore the details of existing and emerging data science platforms, including MapReduce-Hadoop, Spark, and more.

This course will cover contemporary investment strategies, with an emphasis on real-world relevance. The theme of the course will vary depending on instructor interest and expertise. Major topics: fundamental analysis, market efficiency, and computer age investing.

Application of financial models in the business environment. The use of computer-based spreadsheet and simulation packages in business analysis.

An Honors introduction to ethics through issues of medicine and health care. Topics include abortion, treatment of impaired infants, euthanasia, physician-assisted suicide, truth-telling, medical experimentation on human beings and on animals, and the allocation of scarce medical resources. (Gen.Ed. AT)

Contact department for description. (Gen.Ed. AT)