INFO 2770
Last Updated
- Schedule of Classes - June 25, 2020 7:14PM EDT
- Course Catalog - June 25, 2020 7:15PM EDT
Classes
INFO 2770
Course Description
Course information provided by the Courses of Study 2019-2020.
Balancing environmental, economic, and societal needs for a sustainable future encompasses problems of unprecedented size and complexity. Computing and information science can play an important role in addressing critical sustainability challenges faced by present and future generations. The goal of the course is to introduce students to a range of sustainability challenges and to computational methods that can help address such challenges. Sustainability topics include sustainable development, biodiversity and wildlife conservation, poverty mitigation, food security, renewable resources, energy, transportation, and climate change. In the context of these sustainability topics, the course will introduce students to mathematical and computational modeling techniques, algorithms, and statistical methods. The course is at the introductory undergraduate level. Students are expected to have basic knowledge of probability theory and calculus.
When Offered Spring.
Distribution Category (SBA-AG)
Course Attribute (CU-SBY)
Comments Students are expected to have basic knowledge of probability theory and calculus.
Outcomes- Students will be able to identify notions of sustainability as they arise in ecology, geology, economics, and other biological, physical, and social sciences.
- Students will be able to mathematically interpret and calculate levels of sustainability.
- Students will learn how to problem solve techniques of sustainability via computational models, algorithms, and statistical methods.
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Credits and Grading Basis
3 Credits Stdnt Opt(Letter or S/U grades)
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Class Number & Section Details
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Meeting Pattern
- TR M Van Rensselaer Hall G71
- Jan 21 - May 5, 2020
Instructors
Gomes, C
Selman, B
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Additional Information
Instruction Mode: Hybrid - Online & In Person
Prerequisites:Students are expected to have basic knowledge of probability theory and calculus.
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