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Data Science

Master of Science Degree

Companies have access to vast amounts of data - far more than ever before. Leaders need help with making that data useful so informed decisions can be made. They are seeking people with the right expertise to guide them. This program brings together business analytics, visualization, computer science, and statistics to address the entire process of data science.

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Courses in the major include:

This course introduces the possibilities, history, and ethics surrounding Data Science. Basics of data science are explored, including vocabulary, programming languages, big data frameworks, visualization, and statistics. Prior programming experience is not needed for this course.
This course introduces the Python programming language as a tool to clean, slice, and build tools to analyze an existing dataset. Basic principles of programming are explored as well as techniques for configuring a computer for data science work. Prerequisite: Recommend DSC 500
The R programming language and software environment is commonly used for to explore all types of data. Using R, students perform statistical tests on the data. Report writing and presentation of data are introduced. Prerequisite: Recommend DSC 500
This course introduces complex techniques needed for profiling and exploring data. Students use programming and statistics-based inference to ask and answer insightful questions of data. Prerequisite: Recommend DSC 510 and DSC 520
Much like life, the data humans produce is infinitely variable in its structure, presentation, and scale. This course prepares students for this infinite variety of data. Students use Python, SQL, and other tools to acquire, prepare, clean, and automate dataset creation. Prerequisite: DSC 510 or equivalent and recommend DSC 530
Data can often contain patterns and anomalies that only emerge at large scale. In this course, students explore techniques to mine and analyze large datasets to discover useful knowledge. Text mining, unstructured data, social networks, and other types of unsupervised data mining methods for data science are included. Prerequisite: Recommend DSC 540
This course assembles topics covered in previous courses into an applied project. Students have the opportunity to find, clean, analyze, and report on a project they define. Advanced methods of analysis using Python and R allow students to delve deeper into their projects. Prerequisite: DSC 540 or equivalent and recommend DSC 550
Data scientists should be great storytellers, whether using visual, text, or other means. In this course, students explore the basic storytelling components of data science and apply them to different types of data for different types of clients and audiences. Presentation techniques, language use for different audiences, and visualization tools techniques are included. Prerequisite: Recommend DSC 630
This course covers the fundamentals of data infrastructure and how technologies fit together to form a process, or pipeline, to refine data into usable datasets. This course focuses on building a predictive modeling pipeline used by the various types of projects that are called, "big data." Prerequisite: Recommend DSC 540
In this course, students assemble a pipeline to analyze Big Data. Students gather data, then prepare, clean, analyze, and present it to an audience or client in their discipline. Prerequisite: Completion of all other required DSC courses

7 Great Reasons to Consider a Master's Degree

Thinking about earning your master's degree? Here are the top reasons that most people decide to earn their master's degrees.

Your SHRM or HRCI® certification is valued at 6 credit hours (2 courses) toward the Master of Science in Human Resource Strategic Management.

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