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This course teaches the bioinformatics skills used in academic and biotech laboratories for analyzing individual DNA and protein sequences. The focus is extensive hands-on experience using mainstream web-based bioinformatics tools. Laboratory based course that addresses biological questions by analyzing sequences, searching databases, using sophisticated software, and interpreting results. Prerequisites: BIOL 240. (Spring 2024) Core: TI
BIOL 429 Biology Internship (1-3 SH)
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An overview of the various aspects of analytical chemistry such as sampling, statistical analysis of data sets, quantitative and qualitative analysis, spectroscopy and chromatography, and trouble-shooting/ instrument design and maintenance. Emphasis will be given to Gravimetric and Titrimetric analysis, Ultraviolet and visible spectroscopy, Advanced GCMS and ion-selective electrodes. One lecture, four hours of laboratory. Prerequisite: a grade of at least "C" in CHEM 224 and an annual safety training outside of class. (Fall 2024) Core: TI
CHEM 345 Analytical Chemistry II (2 SH)
An overview of the various aspects of analytical chemistry such as sampling, statistical analysis of data sets, quantitative and qualitative analysis, spectroscopy and chromatography, and trouble-shooting/ instrument design and maintenance. Emphasis will be given to Atomic spectroscopy, NMR spectroscopy including multi-dimensional analysis and nuclei beyond C and H, HPLC. One lecture, four hours of laboratory. Prerequisite: a grade of at least "C" in CHEM 224 and an annual safety training outside of class. (Fall 2023) Core: TI
CHEM 405 Thermodynamics (3 SH)
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A lab-based course designed to tour the modern world of computing, this course introduces the major areas of computer science, including data representation, computer hardware, programming languages, algorithms, operating systems, computer networks, and ethics in computing. Core: TI
CS 145 Introduction to Programming (2 SH)
This course provides an introduction to the basic concepts of programming, problem-solving, and design techniques using the object-oriented language Python. Core: TI
CS 155 Programming in Python (2 SH)
Students will apply basic programming concepts with more extensive programs and create a final project of the student's choice in Python. Prerequisite: CS 145 or other programming experience. Core: TI
CS 245 Programming in Java (2 SH)
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An introduction to the design process of an engineering project. The focus will be on different design aspects of an engineering project: defining the design problem, developing a project statement, generating and evaluating ideas and specifications, leading and managing the process, and communicating the outcomes. The design emphasis facilitates students' development of creative and innovation skills, utilizes state-of-the-art technologies, and allows them to experience fields of engineering such as mechanical, electrical, computer, environmental, etc. Core: TI
ENGR 156 Math for Engineering Lab (2 SH)
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This course introduces Geographic Information Systems (GIS) with an emphasis on their role in environmental and conservation practices. Students first learn basic GIS skills in ESRI's ArcGIS 10.3 software and then conduct an independent research project using GIS techniques. Projects may include but are not limited to local natural resource or landscape issues. Independent projects require an oral and poster presentation. Required for students in the environmental science track of the environmental sustainability major. (Spring 2024) Core: TI
ENVS 235 Sustainable Food Systems (2 SH)
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Must be taken concurrently with PHYS 252. Core: NS, TI
PHYS 262 University Physics II Lecture (3 SH)
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Displays of data, measures of center and spread, correlation, normal distributions, and interpretation of statistical tests. Spreadsheets will be used throughout the course. Credit will not be given for both this course and STAT 140. Core: MATH, TI
STAT 133 Topics in Statistics (2 SH)
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This course examines the history, analysis, and creation of data visualizations. Students will learn to critique data visualizations ranging from the simple to the complex, and from the misleading to the powerfully informative. Opportunities to create data visualization will be presented in accordance with each student’s technical skills. CORE: Math, TI
STAT 160 Statistical Methods (3 SH)
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Normal and binomial distributions, confidence intervals, P-values, correlation, and one- and two-sample hypothesis tests, using statistical software. Prerequisite: STAT 120 or instructor approval. (Students wishing to take STAT 220 who have not taken STAT 120 (or an equivalent course) should work through an EMU-provided module that will acquaint them with means, standard deviation, and the standard normal distribution.) Core: MATH, TI
STAT 230 Regression and ANOVA (2 SH)
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