Course Descriptions

QMB1000C Fundamentals of Data Analytics
40 hours, 3 credits

In this course, students will be introduced to the concepts and tools used in current analytics practices. Students will be able to identify common tools, terms, and ideas. Topics covered will include visualization, data quality, platforms, and scripting.

QMB1311C Python Programming
60 hours, 4 credits

In this course, students will work with the Python programming language to learn how it can be used to handle important computing tasks. Students will demonstrate their understanding of flow control, functions, object-oriented concepts, and basic data structures as well as utilizing external modules.

Prerequisite: COP1044C

QMB2200C Fundamentals of Data Visualization
60 hours, 4 credits

This course is an introduction to the concepts and tools used in current visualization methodologies. Students will be able to understand the software and other processes used to produce visualizations. Topics covered will include report design, human perception of visualization, and chart selections rules.

QMB2311C Advanced Python Programming
60 hours, 4 credits

In this course, students will focus on advanced Python techniques and best practices. Through a series of hands-on labs, students will focus on advanced topics to include lambda functions, comprehensions, handling file operations, integration of Regular Expression (regex) logic, and troubleshooting code issues with debugging techniques.

Prerequisite: QMB1311C

QMB3000 Introduction to Data Analytics
60 hours, 4 credits

This course introduces students to the data analytics lifecycle. Students will learn about data sources, data analysis, computing environments, and data ecosystems. Students will compare the key features of various industry tools used to analyze and visualize data. This course describes opportunities and challenges for implementing the data life cycle in a business setting.

Data Analytics Bachelor’s Degree Only - Prerequisites: COP1532C; QMB1311C
Business Management Bachelor’s Degree Only - Prerequisite: CTS3265C

QMB3100 Foundations of Analytics Platforms, Environments, and Software
60 hours, 4 credits

This course explores the different types of environments found in the data analytics space. Topics include a study of the different types of analytics tools used during the data analytics lifecycle and within the Extract Transform Load (ETL) processes in particular.

Data Analytics Bachelor’s Degree Only - Prerequisite: STA1625
Business Management Bachelor’s Degree Only - Prerequisite: STA3215

QMB3200 Introduction to Scripting
60 hours, 4 credits

This course is an introduction to scripting using the online SAS® software suite for accessing, manipulating, analyzing, and visualizing data. Students will learn how to write scripts that are used throughout the data analytics lifecycle to facilitate descriptive and statistical analysis and to produce reports and visualizations that communicate actionable insights to audiences of varying technical backgrounds.

QMB3300 Introduction to Data Visualization
60 hours, 4 credits

This course explores data visualization tools and techniques. It emphasizes the best ways to communicate data to the intended audience. Students learn about tools that aid in visualizing data and how to develop an objective depiction of data using an editorial thinking approach. This course will prepare students for the challenges of having to analyze data and communicate results to audiences with various skill levels and preferences.

QMB4000 Data Elements
60 hours, 4 credits

This course reviews the concepts, standards, and functions used to identify data elements necessary for an efficient data preparation process.

Prerequisite: QMB3200

QMB4100 Applied Business Intelligence
60 hours, 4 credits

This course allows students to apply skills and techniques for analyzing existing business performance data to provide support for business planning. It places focus on planning an end-to-end business intelligence process, platform, database, and analytical tool usage. Students will learn about processing and analyzing data, quality assurance and regulatory adherence, and preparing data for consumption. Students will create visualizations to help guide business decision-making.

Prerequisite: CTS3265C

QMB4200 Advanced Analytics Platforms, Environments, and Software
60 hours, 4 credits

This course covers the data analytics lifecycle surrounding Big Data. Topics include Big Data architectures, batch and real-time processing environments, ETL tools and techniques, Big Data storage technologies, machine learning, and visualization. Security, legal, and ethical issues will also be addressed. Students will work with the SAS® statistical software suite to perform exploratory data analysis and reporting.

Prerequisite: QMB3100

QMB4300 Data Quality in Analytics
60 hours, 4 credits

Quality data allows for quality analysis. In this course, students will learn how to identify common types of data quality issues including missing data, incorrect data, outliers, normalization, and duplication. This course will prepare students to prepare data for analytics projects.

QMB4400 Data Analysis and Optimization
60 hours, 4 credits

This course will allow students to run data extracts and scripts to demonstrate a complete data analysis process, while requiring the identification and application of data element requirements, scripting modifications, and preparation techniques that could improve analysis results.

Prerequisites: QMB4000; QMB4300

QMB4500 Data Visualization Implementation and Communication
60 hours, 4 credits

This course focuses on the study of data sets which relate to meeting client needs. It includes methods used to evaluate data such as benchmarking, scoring, and ranking. Students learn the difference between correlation and causation. Students will explore techniques for visualizing both quantitative and qualitative data. This course will prepare students with the skills to derive business insights and make meaningful inferences from data sets.

Prerequisite: QMB3300

QMB4900 Data Analytics Capstone
60 hours, 3 credits

This course allows students to demonstrate their skills and techniques for analyzing generalized business data to provide support for business planning. It places focus on planning an end-to-end business analytics process; platform, database, and analytical tool usage; processing and analyzing data; quality assurance and regulatory adherence; preparing data for consumption; and visualization creation to help guide business decision-making.

Prerequisite: Expected to be the final upper-level core course completed