The most prominent figure in India's anti-colonial nationalist movement, Mahatma Gandhi has also been one of the most remarkable global leaders and thinkers of the twentieth century. Charting Gandhi's trajectory against the background of events in South Africa and colonial India, this course examines the ideas, strategies, achievements and limitations of Gandhian politics. Using a variety of written sources and films, we will critically assess Gandhi's influence on and conflicts with various streams of anti-colonial nationalism(s) in India.

This is the second semester of biomedical engineering capstone design sequence. The scope of biomedical engineering design and development encompasses a wide variety of scientific and engineering fields. This is a project based course utilizing fundamental concepts involved in biomaterials, biomechanics, bioinstrumentation to solve biomedical engineering problems. In this course students will build upon their capstone design project from Senior Design I with engineering analysis and design optimization of their selected design concept, prototyping, testing, reporting and oral presentations.

An introduction to kinesiology with specific applications to dance. We will attend to fundamental principles of human anatomy, biomechanics, motor development, and motor learning. We will establish a working lexicon for articulating musculoskeletal structures involved in simple action sequences. We will define motor learning theories and discuss motor development trajectories, along with illustrations of their dance-specific applications from the scientific literature. Labs will focus on acquiring skill in administering motor development assessments and functional tests.

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.