College of Engineering, Informatics, and Applied Sciences2021-2022

School of Informatics, Computing and Cyber Systems

Informatics, Master of Science

Learning Outcomes

Purpose Statement

This M.S. in Informatics will prepare you to either enter the informatics workforce or continue on to a doctoral program of study, building core skills that are widely applicable to many areas of science.
 
Core coursework provides learning opportunities in the foundations of informatics, programming and computer science, structuring large-scale data sets, machine learning, and statistical data analysis. Elective coursework allows students to customize their program of study so that it is maximally aligned with their professional or research interests, with coursework available in many areas of informatics, including epidemiology, bioinformatics, ecological modeling, and remote sensing. Thesis option students will have additional opportunities to engage in informatics research and scholarship under the mentorship of an informatics faculty member as prepare a thesis on their specific research.
 
This program is designed for students with strong preparation in an area of science, such as biology or ecology, and experience in computer programming and data analysis gained through successful completion of a relevant undergraduate program or other professional experience. The non-thesis option of the program is designed for students seeking professional preparation, while the thesis option is particularly appropriate for students for considering further graduate study in a doctoral program.
 
As a graduate, you will be prepared to contribute in a wide variety of informatics areas, including population health, bioinformatics, remote sensing, ecological modeling, wearable computing, and machine learning and data science.

Student Learning Outcomes
 

  • Graduates of this program will demonstrate the following competencies and program learning outcomes:
  • Identify, explain, and synthesize fundamental concepts of informatics, including population health, bioinformatics, remote sensing, ecological modeling, wearable computing, and machine learning and data science
  • Analyze and critically distill scientific literature to identify informatics theories and development and research methods appropriate to relevant science problems and research areas
  • Apply informatics theories and development and research methods to formulate, develop, and assess informatics solutions to relevant science problems and research areas
  • Compose and engage in highly effective written and oral communication in informatics areas that demonstrates clear argumentation and logical cohesion

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