ANLT5010
Foundations in Analytics
4 quarter credits
Learners in this course apply data management fundamentals to data models. Learners examine the concepts of data mining, ETLs, and data warehouses and also evaluate applied analytics in professional domains such as finance, marketing, and health care. Prerequisite(s): Completion of or concurrent registration in ANLT5002 or ITEC5020.
4 quarter credits
ANLT5020
Data Sources for Analytics
4 quarter credits
In this course, learners explain database methodologies including relational databases, flat files, dimensional modeling, RSS feeds and multi-dimensional modeling. Learners examine the impact of data quality on analytics and apply ETL techniques and processes. Finally, learners evaluate the application of data warehouses, data marts, and multi-dimensional cubes to decision-making and action. Prerequisite(s): Completion of or concurrent registration in ANLT5010 or HMSV5500.
4 quarter credits
ANLT5030
Statistical Methods in Analytics
4 quarter credits
In this course, learners study the collection, organization, presentation, analysis, and interpretation of data using statistical methods. Learners practice using appropriate tools to obtain a result using statistical methods and collaborate with team members to compare processes, techniques, and conclusions to understand various perspectives. Prerequisite(s): Completion of or concurrent registration in ANLT5020 or HMSV5510.
4 quarter credits
ITEC5040
Predictive Models and Classification Methods
4 quarter credits
Learners gain the skills to utilize historical data to predict future outcomes, as well as identify patterns in current data that can be used to classify or group future observations. Learners complete their own analytics project through hands-on statistical techniques coupled with a broad understanding of contemporary predictive modeling and analytics classification methods.
4 quarter credits
ANLT5100
Visual Analytics
4 quarter credits
In this course, learners articulate the value of visualization to telling the analytic story to stakeholders. Learners explore the appropriate presentation of types of data and apply best practices for the design of effective visualizations. Learners also develop skills for presenting data to stakeholders in a succinct and relevant manner. Prerequisite(s): ANLT5030.
4 quarter credits