DATA 101 - Introduction to Data Science

Fundamental coursework on the standards and practices for collecting, organizing, managing, exploring, and statistically analyzing data. Topics include preparation, analysis, and modeling of data, the basics of machine learning, and creating analysis tools for larger data sets. PREREQUISITE(S): A grade of C or better in MATH 117, MATH 217, BSAD 210 or consent of department. Three hours each week.

3 semester hours

Course Outcomes:
Upon completion of this course, a student will be able to:

Identify and describe the methods and techniques commonly used in data science.
Demonstrate methods and techniques for obtaining, organizing, exploring, and analyzing data.
Recognize how data analysis, inferential statistics, modeling, machine learning, and statistical computing can be utilized in an integrated capacity.
Create and modify customizable tools for data analysis and visualization per the evaluation of characteristics of the data and the nature of the analysis.
Obtain and assemble data from a variety of sources.
Clean and wrangle data for exploration and analysis.
Evaluate and apply ethical principles and practices in the data lifecycle.

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