Data Analytics analyzes vast databases that must be examined using complex algorithms and artificial intelligence to identify previously unidentified useful sets of relationships and trends. The Data Mining and Visualization Graduate Certificate is offered online and prepares individuals to conduct data mining projects, generate data visualization products, and build data dashboards and automated reports. The concentration uses industry standard software in practical applications directly related to current trends and issues that impact organizations across a broad spectrum. Course progression and content is carefully formulated to build competency in data mining and visualization for students from a broad range of disciplines and experiences, including those who are new to the field. Credit from this certificate program can be transferred to the Master of Science in Data Analytics Degree program.
Recommended Prerequisite: DATA610 Essentials of Business Analysis (3 cr) is a recommended prerequisite that should be completed prior to taking the following courses in the Graduate Certificate in Data Mining and Visualization.
DATA courses are only offered in a 15-week online format.
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. Students will also learn how data mining can be effectively used in various application areas to drive decisions and actions. Students get hands-on practice by conducting a data analytics project using real world data sets.
Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
R programming language concepts are covered within the context of how they are implemented in practice when conducting high-level statistical analysis. The instructional approach in this course focuses on application-based programming concepts 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 will be used to provide working examples. Upon completing this course, students will be able to employ advanced modeling techniques to write R code to conduct data analysis with strong reusability.
This course will be a more advanced treatment of data mining and predictive analytics concepts introduced in DATA625 with a focus on customer relationship management (CRM). Using customized variations of the industry-standard CRISP-DM methodology, it will provide an experiential learning opportunity to explore all six phases of the model. This includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Industry standard tools and techniques are utilized to prepare students with the knowledge to be successful in current organizations. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
Prerequisite(s): DATA625