Data Analytics (DATALTIC GRC)
12 Credits
GRADUATE CERTIFICATE • 12 CREDITS • DATALTIC GRC
Data Analytics is used to analyze vast databases that must be examined using complex algorithms and artificial intelligence to identify previously unidentified useful sets of relationships and trends. All aspects of the business and medical communities, as well as government agencies and non-profit organizations rely on data analytics, yet are hampered by a growing shortage of data analysts. Davenport’s 12 credit Graduate Certificate in Data Analytics responds to this need by preparing individuals to conduct data mining projects, generate data visualization products, and build data dashboards and automated reports. Using industry standard software, graduates get hands-on experience in practical applications directly related to current trends and issues that impact organizations across a broad spectrum. Credit from the certificate program can be transferred to the Master of Science in Data Analytics Degree program. Courses for are offered online in 15 week format with two courses completed per semester.
DATA courses are only offered in a 15-week online format.
Which class should I take? When should I take it?
See our Recommended Program Sequences:
Courses |
12 Credits | |
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DATA610 | This course introduces advanced methods of building statistical models for decision-makers, with a primary focus on modeling techniques such as logistic regression and discriminant analysis. Students solve real-world business cases, applying statistical concepts and techniques in business, finance, market research, and healthcare management contexts. | |
DATA625 | This course introduces students to data mining methods and applications. It covers basic concepts and tools for data mining, including data sources, data cleaning tools and methods, mainstream algorithms for data mining, statistical modeling, popular tools for mining structured data and unstructured data. Through hands-on practice conducting data analytics projects using real world data sets, students also learn how data mining can be effectively used in various application areas to drive decisions and actions. | |
DATA667 | In this course, students learn data visualization and communication skills using industry standard software. Emphasis is placed on communicating practical implications of data analytics results to a non-technical audience to facilitate decision making. Students apply their learning through hands-on projects, creating reports, and dashboards with high-impact visualizations. | |
DATA710 | In this course, students learn R programming language concepts in the context of conducting high-level statistical analysis through application-based programming such as reading data into R, accessing analysis tool boxes in R, writing R functions, debugging, and organizing and commenting in R code. Data mining and analysis projects provide students working examples through which to apply various analysis strategies. Ultimately, students employ advanced modeling techniques to write R code to conduct data analysis with strong reusability. |