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Computing and Data in Practice — CS4389.01

Instructor: Michael Corey
Days & Time: Tu 8:30AM-10:20AM
Credits: 2

For students doing work-study or internships, we will focus on three core areas of professionalization. First, each week will journal our work weeks, discussing and sharing our work experiences in a round-table. Second, we will build our professionalization skills, especially networking (in person and on LinkedIn), resume writing, and doing practice interviews. Finally, we will work on writing 5-year plans, to help us figure out where we鈥檇 like to be a few years after graduation. More specifically

Data Structures and Algorithms — CS4388.01

Instructor: Darcy Otto
Days & Time: TU,FR 2:10pm-4:00pm
Credits: 4

How do we organize data to solve complex problems efficiently? This course studies the fundamental structures and algorithms that form the cornerstone of computational problem-solving. Building upon the programming foundations established in CS1, we will explore how algorithmic thinking and sophisticated data organization enables us to tackle increasingly challenging computational problems.

Scanning Electron Microscopy Research Methods — ES4107.01

Instructor: Tim Schroeder
Days & Time: TU 2:10pm-4:00pm
Credits: 2

Scanning electron microscopes are a fundamental tool in the physical and life sciences. When equipped with an X-Ray spectrometer, a SEM can provide rapid physical and chemical data of specimens on extremely small scales. This class with cover the theory and practical applications of SEM imaging and analysis for advanced science students who have their own research interests. Students will be expected to develop and conduct an independent research project through this class.