Introduces the basic concepts, methodologies, and research findings in information retrieval. Special topics include Web searching, cross-language retrieval, data mining, and data extraction. Completion of this course will provide the necessary foundation to work in today's business environment where competitive advantage is obtained by retrieving needed information.

How does Neflix learn what movies a person likes? How do computers read handwritten addresses on packages, or detect faces in images? Machine learning is the practice of programming computers to learn and improve through experience, and it is becoming pervasive in technology and science. This course will cover the mathematical underpinnings, algorithms, and practices that enable a computer to learn. Topics will include supervised learning, unsupervised learning, evaluation methodology, and Bayesian probabilistic modeling.

An introduction to the issues involved in orchestrating the use of computer resources. Topics include operating system evolution, file-handling systems, memory management, virtual memory, resource scheduling, multiprogramming, deadlocks, concurrent processes, protection, and design principles. Course emphasis: understanding the effects of operating system design on computer system performance. This course is programming intensive.

Most of the environmental challenges we face are complex and interdisciplinary in nature. This course introduces students to the scientific principles, concepts, and methodologies required to both understand the interrelationships of the natural world, as well as to identify and analyze environmental problems and think critically about alternative solutions for addressing them. Key concepts from ecology, biogeochemistry, and other scientific fields inform our study of climate change, water resources, soil sustainability, food production, and other topics.

How does Mapquest find the best route between two locations? How do computers help to decode the human genome? At the heart of these and other complex computer applications are nontrivial algorithms. While algorithms must be specialized to an application, there are some standard ways of approaching algorithmic problems that tend to be useful in many applications. Among other topics, we will explore graph algorithms, greedy algorithms, divide-and-conquer, dynamic programming, and network flow.

This course helps students attain a higher level of proficiency in modern Japanese through the extended use of the language in practical contexts. The class will be conducted mostly in Japanese.

This course advances students' Chinese reading, writing, listening, and speaking skills by studying journalistic reports on the most pressing issues in China and the U.S. It also introduces the formal expressions, writing styles, and terminology commonly used in Chinese media.

This course is a discussion and practicum for students currently acting as mentors in the Computer Science Megas and Gigas Educate (MaGE) peer mentoring program. Through discussion, we will draw connections between the peer mentor experience and existing research and philosophies of peer mentoring and computer science education, to develop effective practical strategies.

This course helps students to build linguistic and communicative competence in Mandarin Chinese through reading, discussing, and writing about authentic texts. Newspapers, essays, and short stories will be the teaching materials for the course. An interactive approach will be incorporated into the curriculum to improve students' conversational skills. The class will be conducted mostly in Chinese, and class hours will be supplemented by individual work in the Language Resource Center.