MSDA Curriculum

First, choose your program:

100% Online MSDA

• MSDA curriculum will be taught 100% online and you are given registration priority for online classes.

Flexible MSDA

• Offers a mix of face-to-face courses (taught during the evening hours) and online course options.

Learn more about our Master of Science in Data Analytics curriculum as well as any prerequisites for an MSDA that may be required.

Core Courses

Program Coursework: Required Core Courses

Core Courses
(7 total courses; 21 credit hours total required)

DATA 5110 - Programming and Data Preparation for Analytics: This course introduces programming concepts and techniques for business data analytics. Topics include coding with industry-standard programing platforms to read data from various sources, explore, manipulate and prepare data for developing machine learning models.

DATA 5120 - Descriptive Analytics: This course introduces students to descriptive analytics, a vital component of business analytics that focuses on summarizing, exploring, and understanding business data. Students will learn how to use statistical methods and techniques to analyze business challenges and derive actionable insights. The course will cover techniques such as data summarization, correlation, regression analysis, and time series analysis. Prerequisite: Successful completion of online background module in business statistics or academic advisor approval based on academic record is required.

DATA 5140 - Databases and Data Warehouses: This course provides comprehensive coverage of operational and analytical databases, emphasizing essential database management skills required for business analytics. Topics include conceptual database design using entity-relationship modeling (ERD), logical database design through normalization, and physical database implementation. Students will learn to design data warehouses and data marts using star schema methodology and explore Extract, Transform, and Load (ETL) processes to integrate operational data into analytical platforms. Hands-on sessions with MySQL in a laboratory setting will equip students with practical skills to create, query, update, and retrieve data from SQL databases.

DATA 5150 - Data Visualization for Business: This course covers development of effective visualization to facilitate the understanding of complex organizational data. Topics include human perception & attention, visualization software & toolkits, visualization techniques for spatial data, geospatial data, time-oriented data, multivariate data, trees, graphs, networks, maps and text. Evaluate good design practices for visualization. Review cutting-edge research in data visualization.

DATA 5230 - Introduction to Machine Learning: This course provides a structured approach to machine learning, covering key principles, model development, and performance evaluation. Students will learn to assess predictive and classification performance while applying strategies to mitigate overfitting, handle rare events, and address unequal classification error costs. Through hands-on exercises, they will build and evaluate models such as k-NN, Naïve Bayes, Decision Trees, Regression, and Neural Networks, gaining practical skills for real-world applications. The course leverages leading-edge software platforms to implement machine learning techniques, ensuring students gain experience with industry-standard tools. Prerequisites: DATA 5110 and DATA 5120

DATA 5240 - Advanced Machine Learning: This course offers a comprehensive exploration of advanced machine learning techniques for solving real-world business problems. Students will gain expertise in SVMs, deep learning frameworks, and natural language processing (NLP) for tasks such as sentiment analysis and text classification. The course also covers hyperparameter tuning with Grid Search, Random Search, and Bayesian optimization. Through a hands-on, real-world project, students will apply these techniques using leading-edge software platforms, analyze results, and deliver actionable insights to tackle complex business challenges. Prerequisites: DATA 5230

DATA 5250 - Big Data Management and Analysis: This course covers the core concepts behind big data problems, applications, and systems. It introduces one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible. Topics include a discussion of the Big Data landscape, examples of the real world big data problems, architectural components and programming models used for structured and unstructured big data analysis, HDFS file system, MapReduce, YARN, PIG, HIVE, NOSQL, and other Big Data programming techniques or platforms. Prerequisite: DATA 5140

Project or Internship

(3 to 6 credit hours)*:

*Students who take 3 credit hours of project or internship coursework are required to complete 4 elective courses (12 elective credit hours). Students approved to take 6 credit hours of project and/or internship coursework are required to complete 3 elective courses (9 elective credit hours).

Students can choose to do the following:

Students can choose an Internship with a company for either three or six credits. The internship should not be from the job they are performing with their current employer (if applicable). A faculty member must approve the internship.

Students can complete a Capstone Project involving data collection, cleaning, analysis, model development, and evaluation. The capstone project can be individual or a group of up to three students. The Capstone Project can be for three credit hours.

DATA 5920r (3 Credit) - Internship: (Can be repeated up to two times): Students can do a one or two semester internship with a company to gain real world experience in data analytics.  The internship should represent significant work and will be jointly supervised by a faculty member from UTC and a company representative.

DATA 5930 (3 Credit) - Capstone Project: This course provides students with an opportunity to integrate all the knowledge learned in the Master of Science in Data Analytics program by working on a comprehensive project. The project will involve data collection, cleaning, analysis, model development, and evaluation.

Elective Courses

Students can take courses in a variety of subjects as part of the MS Data Analytics program.

Elective Course Options

Students choose 3 or 4 courses from following depending on internship or practicum project selected.

ACC 5855 - Accounting for Managers:  The purpose of this course is to provide students with a thorough exposure to the basic elements of financial and managerial accounting from a manager’s perspective.  Emphasis is placed on the application of accounting information both from an external user’s perspective and for internal decision making. Contemporary topics that might affect the use of accounting information are surveyed, including in depth discussion of current events in business and financial news.  The course draws upon the collective business experiences of the participants during classroom discussions that demonstrate the application of key concepts.

CPSC 5130 - Cloud Computing: Cover advanced web technologies, distributed computing models and technologies, Infrastructure-as-a-service (IaaS), Software as a Service (SaaS), Platform-as-a-service (PaaS), virtualization, parallelization, security/privacy, and current challenges.

CPSC 5610 - Advanced Information Security Management: Cover advanced web technologies, distributed computing models and technologies, Infrastructure-as-a-service (IaaS), Software as a Service (SaaS), Platform-as-a-service (PaaS), virtualization, parallelization, security/privacy, and current challenges.

DATA 5180 - Prescriptive Analytics: This course covers a survey of optimizations and decision making techniques and offers practical recommendations for using these tools for operational business intelligence.

ECON 5015 - Economics for Managers:  Economics for Managers uses real-­world issues and examples to illustrate how economic principles impact business decisions. Emphases on agency and contract theory, managerial behavioral economics, game theory, and pricing are especially valuable to decision making by managers. In this course, cases use actual data to illustrate the use of basic economic models to solve managerial and economic problems.

FIN 5820 - Financial Management:  The goal of this course is to acquaint students with the primary concepts and techniques of financial analysis. The course will build upon the skills obtained in accounting and economics and use those skills for making decisions regarding a firm’s use of capital toward the goal of maximizing the value of the firm. It is assumed that all students are familiar with financial statements and basic statistical and economic principles. The first part of the course will develop the tools used in modern financial analysis, including financial statement analysis and valuation techniques. Latter portions will apply these tools to decision-making for long-term (capital budgeting and cost of capital) financial management for both large and small firms.

MGT 5050 - Evidence Based Management & Improvement in Healthcare: This course examines the role of managers in leading change and supporting improvement efforts within their organization. Special focus will be placed on the importance of working with professionals from across the healthcare environment to maintain improvements over time while balancing the inherent conflict between rising costs and patient expectations. Students will examine the use of different improvement techniques including: lean management, six sigma, customer satisfaction, quality control, high reliability performance, and evidence based protocols. Students will evaluate professional literature and external industry standards to benchmark internal organizational performance against as well as inform improvement effort designs. Students will design a quality/process improvement project to address issues in healthcare delivery and present their quality improvement plan.

MGT 5060 - Healthcare Management: This course explores the challenges that managers experience within complex healthcare organizations including the impact of diverse employee and professional groups on work. Readings and class discussions focus on understanding key management functions (such as planning, staffing, and organization) balanced with mission, financial, and regulatory constraints. Students will examine current issues faced by hospitals, clinics and other healthcare organizations. Current events and cases will be used by students to apply concepts discussed in class.

MGT 5070 - Health Informatics Research Methods: Healthcare informatics is critical for enabling better collaboration and coordination among healthcare providers, streamlining medical quality assurance processes, improving cost-efficiency in healthcare delivery and increasing accuracy and efficiency in facility/practice management.

MGT 5250 - Organizational Behavior and Leadership: An examination of the theoretical and research foundations that explain behavior within the context of organizations. The focus will be on how organizational behavior theory is translated into practice such that students will acquire the knowledge and skills necessary to become an effective manager.

MKT 5610 - Digital Marketing: The internet is a dynamic marketplace if there ever was one. This class will give you a theoretical understanding of the internet marketplace that is necessary to adapt to its many changes while equipping you with the skills you’ll need to perform vital daily functions. By the end of the course, you will be able to walk into any company with an online presence and improve its use of the internet. This course introduces students to the changing landscape of digital media and its use as a new tool in the marketing mix. The course will explore digital marketing tangibly and conceptually, its appropriate use as part of a comprehensive marketing plan, and give students a framework for adapting to the rapid changes in these mediums. The objective of this course is to provide knowledge of how to strategically think about deploying marketing initiatives through digital marketing. This course is aimed at students considering a career in the digital marketing field in various sectors (writing, design, social media, SEO, email, search, etc.) or in any profession where digital marketing can be applied.

MKT 5860 - Marketing Management: The goal of this course is to provide a decision-oriented overview of marketing management. This course focuses on the management challenge of designing and implementing marketing strategies that maximize customer satisfaction and firm profitability.