Helzberg School MS-DA Curriculum
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The M.S. in Data Analytics curriculum consists of 26 core credit hours, 4 credit hours of electives of your choice and any prerequisite courses needed.
On-campus classes meet once per week from 5:45 to 9 p.m., Monday through Thursday. Online classes typically require weekly assignments to be completed within a specified window on the student's schedule. Most students take two courses per semester. See course descriptions below.
Core Courses
- Business Intelligence, BIA 6300 (2 credit hours)
- Applied Data Mining, BIA 6301 (2 credit hours)
- Data Visualization, BIA 6302 (2 credit hours)
- Predictive Models, BIA 6303 (2 credit hours)
- Text Mining, BIA 6304 (2 credit hours)
- Big Data Analytics, BIA 6305 (2 credit hours)
- Web and Social Media Analytics, BIA 6306 (2 credit hours)
- Performance Metrics and Dashboards, BIA 6307 (2 credit hours)
- Analytics and Strategy, BIA 6308 (2 credit hours)
- Managerial Communications, MG 6008 (2 credit hours)
- Financial Decision Making for Managers, ACFN 6300 (2 credit hours) -OR- Financial Analysis, AC 6110 (2 credit hours)
- Project Management, MG 6320 (2 credit hours)
- Marketing Strategy, MK 6410 (2 credit hours) -OR- MK 6460 Marketing Research and Analysis (2 credit hours)
Core courses already taken through another degree program can be substituted with an additional elective. Program director consent is required.
Course Descriptions
BIA 6300. Business Intelligence (2 credit hours)
Business leaders must have the ability to collect and interpret information concerning customers, suppliers and competitors, and make decisions that affect their company's performance. Business intelligence is a set of methodologies, processes, architectures and technologies that transform raw data into meaningful and useful information to enable more effective strategic, tactical, and operational insights and decision-making with an emphasis on knowledge management. Using the case study approach in combination with contemporary software tools, students will apply the concepts of business process analysis, quality control and improvement, performance monitoring through performance dashboards and balanced scorecards, as well as process simulation.
6301. Applied Data Mining (2 credit hours)
Applied Data Mining introduces students to supervised and unsupervised machine learning methods. Supervised methods include linear regression, logistic regression, k-nearest neighbor, Naïve Bayes, and decision trees. Unsupervised methods include cluster analysis and association rules. Data preparation, dimension reduction, and model performance evaluation are also examined. Emphasis is placed on working with large data sets in a business context and communicating results to diverse audiences. The primary software used is R but other tools may be incorporated. Prerequisite: BIA 6201, BIA 6202, and BIA 6203, or consent of the Program Director.
BIA 6302. Data Visualization (2 credit hours)
This course is about the interactive exploration of data, and how it is achieved using state-of-the-art data visualization software. Students will be able to present complex quantitative and qualitative data visually. Participants will learn to explore a range of different data types and structures. They will learn about various interactive techniques for manipulating and examining the data and producing effective visualizations. Participants will be guided through an exploration of quantitative business data to discern meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities. Data visualization is both an art and a science. It is an art concerned with unleashing creativity and innovation, designing communications that appeal on an aesthetic level and survive in the mind on an emotional one. Statistics and exposure to any programming language are required. The primary software tool for this class will be Tableau. Prerequisite: BIA 6300.
BIA 6303. Predictive Models (2 credit hours)
The course examines advanced machine learning methods. Students learn to build, train, and validate predictive models. Topics include model tuning, regularization, support vector machines, ensemble models, neural nets, Bayesian analysis, Markov Chain Monte Carlo (MCMC) methods, and recommender systems. Emphasis is placed on working with large data sets and communicating results to diverse audiences. The primary software used is Python. Other topics and software may be incorporated. Prerequisite: BIA 6301.
BIA 6304. Text Mining (2 credit hours)
This course will introduce the essential techniques of text mining, sometimes referred to as text analytics, which involves the retrieval and preparation of text for use with data mining’s standard predictive methods. Students will be introduced to methods to extract text from a variety of sources (e.g. web, social media, documents) and will learn how to process text and build a corpus to appropriately address business questions. Students will also be introduced to sentiment analysis, document similarity, and topic modeling. The primary software tool for this class is Python. Prerequisite: BIA 6301 is required; and BIA 6303 is recommended.
6305. Big Data Analytics (2 credit hours)
This course will emphasize different hardware architecture and transformation and preparation and analytics of big and complex data. Students will be introduced to data wrangling and munging of both structured and unstructured from traditional relational databases as well as more complex storage systems (such as Hadoop). Students will also be introduced to parallel processes for big data such as map reduce as well as different query languages. Students will use a variety of big data platforms to process, analyze and present data. Several programming languages will be used including Python and Linux. Prerequisite: BIA 6301 is required; and BIA 6303 is recommended.
BIA 6306. Web and Social Media Analytics (2 credit hours)
The primary focus of the course is the application of descriptive and predictive techniques to web analytics and other social media platforms including user behavior modeling and e-metrics for business intelligence. Students will also work with Google analytics and other web-based analytical platforms to judge performance and ROI of a company’s web and social media programs. The primary software tool for this class will be Google Analytics and other web-based tools. Prerequisite: BIA 6300, BIA 6301 and BIA 6302 or consent of the program director.
BIA 6308. Analytics and Strategy (2 credit hours)
The focus of this class is the implementation of analytics as a competitive advantage across the enterprise. In this course, students will read case studies and hear from guest speakers about challenges and opportunities generated by the advent of “big data.” Students will make group presentations and write critical response papers related to these case studies. Students will consider some of the traditional business frameworks (e.g., SWOT analysis) for evaluating the strategic opportunities available to a company in the “big data” space. Prerequisite: BIA 6300, BIA 6301 and BIA 6302 or consent of the program director.
BIA 6307. Performance Metrics and Dashboards (2 credit hours)
A simulation-based course designed to provide students with experience through the full performance management life-cycle. Using case study data, students will evaluate a real-world business issue and apply analytic models to identify areas for improvement. Students will design metrics to measure performance and implement monitoring dashboards to determine if their hypotheses are effective through a simulation. Students will then develop business reports to demonstrate the effectiveness of analysis, metric/Key Performance Indicators development, and executive reporting. Prerequisite: BIA 6300 and BIA 6302 or consent of the program director.
MG 6008. Managerial Communications (2 credit hours)
To explore the various techniques, instruments, processes, and styles employed by leaders to communicate effectively within organizations. Students write, give oral presentations, and learn how to employ electronic media effectively. Exercises employ numerous real or simulated business situations that require communication in different styles, using a variety of forms and methods. This course is designed to provide an introductory experience and orientation to the MBA and establish common communication protocols, determine critical self-awareness profiles, and identify the Rockhurst themes that will be applied throughout the program.
ACFN 6300. Financial Decision-Making for Managers (2 credit hours)
This course is an investigation of financial decision-making in business, government, and not-for-profit organizations. Emphasis is on the application of financial and nonfinancial information to a wide range of management decisions, from product pricing and budgeting to the project analysis and performance measurement. A variety of decision-making tools such as break-even analysis, activity-based costing procedures, contribution margins, budgeting and the balanced scorecard are included. Emphasis is also placed on preparing financial information to request new capital, personnel or projects. This course will focus on the interpretation and use of basic financial information by non-financial managers, not on production of financial statements and reports. Only open to students enrolled in the Masters in Management program and MSN in Leadership program.
MG 6320. Project Management (2 credit hours)
This course introduces students to the process of project management that includes planning, implementation, progress measurement and performance, results and evaluation. Students will learn the knowledge, skills and technical tools for identifying project requirements, establishing project objectives and scheduling, balancing constraints and resources, and considering the needs and expectations of key stakeholders. Students will learn the trade-offs and balance of project scope, resources and schedule, and will learn how to compose an effective project management team. The course also covers producing project documentation, such as scope, requirements, design and testing documentation.
Choose one Marketing course for the core requirement:
MK 6410. Marketing Strategy (2 credit hours)
This strategic marketing course gives you practice in the design, implementation and control of marketing strategies. It is an operationally oriented course in which the application and not the definition of marketing concepts, principles and methods are important. The course stresses the integration of the major decision areas of marketing rather than the sequential discussion of these subjects.
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