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Medford, Andrew J.; Boukouvala, Fani; Grover, Martha A.; Sholl, David; Meredith, Carson; Cheng, Pengfei; Choi, Sihoon; Gusmão, Gabriel S.; Kilwein, Zachary; Ravutla, Suryateja; Wirth, Fatimah; Wooley, Jennifer; Sewer, Zaid – Chemical Engineering Education, 2022
The Graduate Certificate in Data Science for the Chemical Industries was designed to provide skills to working professionals, via a fully online and asynchronous format. The certificate may also be earned by undergraduate and graduate students at Georgia Tech. The certificate consists of four courses. The two core courses are Data Analytics for…
Descriptors: Chemistry, Science Instruction, Statistics Education, Chemical Engineering
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Johnson, Marina E.; Misra, Ram; Berenson, Mark – Decision Sciences Journal of Innovative Education, 2022
In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…
Descriptors: Bayesian Statistics, Programming Languages, Artificial Intelligence, Data Analysis
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Yoshida, R.; Page, R. – PRIMUS, 2022
In the fall of 2009 and in the spring of 2012, supported by the National Institute of General Medical Sciences (NIGMS) in the National Institutes of Health (NIH), we designed a course "Phylogenetic Analysis and Molecular Evolution" (PAME), the first cross-listed course across three different colleges (College of Arts and Sciences,…
Descriptors: Molecular Biology, Evolution, Molecular Structure, Graduate Students
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Hong, Moo Sun; Sun, Weike; Anthony, Brian W.; Braatz, Richard D. – Chemical Engineering Education, 2022
This article describes experiences with teaching process data analytics and machine learning, including in: (1) a joint undergraduate/graduate course for students in chemical and mechanical engineering and engineering management; and (2) an undergraduate chemical engineering concentration in process data analytics. The article also describes…
Descriptors: Teaching Methods, Graduate Students, Undergraduate Students, Chemical Engineering
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Bertrand Schneider; Joseph Reilly; Iulian Radu – Journal for STEM Education Research, 2020
In an increasingly data-driven world, large volumes of fine-grained data are infiltrating all aspects of our lives. The world of education is no exception to this phenomenon: in classrooms, we are witnessing an increasing amount of information being collected on learners and teachers. Because educational practitioners have so much contextual and…
Descriptors: Learning Analytics, Classroom Techniques, Multimedia Materials, Graduate Students
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Mike, Koby; Hazzan, Orit – Statistics Education Research Journal, 2022
Data science is a new field of research that has attracted growing interest in recent years as it focuses on turning raw data into understanding, insight, knowledge, and value. New data science education programs, which are being launched at an increasing rate, are designed for multiple education levels and populations. Machine learning (ML) is an…
Descriptors: Teaching Methods, Nonmajors, Statistics Education, Artificial Intelligence
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Reinhart, Alex; Genovese, Christopher R. – Journal of Statistics and Data Science Education, 2021
Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…
Descriptors: Computer Software, Graduate Students, Computer Science Education, Statistics Education
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Beckman, Matthew D.; Çetinkaya-Rundel, Mine; Horton, Nicholas J.; Rundel, Colin W.; Sullivan, Adam J.; Tackett, Maria – Journal of Statistics and Data Science Education, 2021
A version control system records changes to a file or set of files over time so that changes can be tracked and specific versions of a file can be recalled later. As such, it is an essential element of a reproducible workflow that deserves due consideration among the learning objectives of statistics courses. This article describes experiences and…
Descriptors: Statistics Education, Data Analysis, Teaching Methods, Graduate Students
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Radovilsky, Zinovy; Hegde, Vishwanath – Journal of Information Systems Education, 2022
Data Mining (DM) is one of the most offered courses in data analytics education. However, the design and delivery of DM courses present a number of challenges and issues that stem from the DM's interdisciplinary nature and the industry expectations to generate a broader range of skills from the analytics programs. In this research, we identified…
Descriptors: Data Analysis, Statistics Education, Graduate Students, Barriers