Online Master of Science in Business Analytics Curriculum
The Online MSBA program from Seattle University is designed to prepare you for the realities of messy data sets and unclear business obstacles. Develop key quantitative skills, including R and Python programming, Apache Hadoop and Spark, SQL, and more. At Albers, we know that your success in business analytics requires that you hone your communication and leadership skills alongside your technical capabilities. The Online MSBA will challenge you to master written, oral, and visual communication so that upon completing the program, you will emerge as an ethical and adaptive leader of business analytics, able to translate data into decisive action.
Data Translation Challenges
Each Online MSBA course incorporates one or more Data Translation Challenges designed to help you develop a methodological approach to data analysis geared toward its eventual presentation to a diverse business audience.
In each of these assignments, you will follow a three-step approach for analyzing and understanding complex data and synthesizing that data to develop informed business strategies:
- Consider a business problem derived from real-world data sets and scenarios
- Analyze the data using computational tools
- Communicate your findings and recommendations via written, oral, and/or visual methods
While Data Translation Challenges may vary in size and significance to your grade from class to class, each one is designed to model the business challenges you will likely face in an analytical role and help you grow into a data-fluent, multifaceted professional who can overcome them.
Sample the Online Experience with a Course Demo
Hello, my name is Jac Cooper, and I will be your student success coordinator on behalf of Seattle University.
In this video, I will be briefly talking with you about OMSBA 5067: Machine Learning and Business course. I'll be sharing my screen and showing you some key resources that will help you through the program. By selecting the Start Here button, you'll learn more about the course itself and the goals and learning outcomes that have helped design the course structure.
At the top of your screen, you'll see a tab labeled Syllabus/Text. If you click on this tab, then you'll be able to access the syllabus for this course. The syllabus in many ways is the contract for the course. It gives you the breakdown of assignments in the course. It gives you the breakdown of the grades and the assignments in the course.
However, some of the most important information you can pull from your syllabus is your instructor's contact information. The next resources you should explore is the Extras tab. Within this tab, you can find technology tips that will be pivotal when completing an online degree program.
On the left-hand side of your screen, you'll see the word "Modules." When you click on this link it will take you to a breakdown of some of the information we've already discussed, such as the course description, instructor information, tech support, and the syllabus.
However, as you scroll down the page, you'll see more supportive resources listed.
The instructors office hours, sample exams, and a week-by-week breakdown of information that will be covered, such as assignments, discussions, class activities and practices quizzes. The university and your instructor have worked to put forward a wealth of information so that you feel fully prepared to be successful in this course and program.
By giving you all the resources and timeline of assignments is the goal of the OMSBA program to allow you to know how to fully integrate your school schedule into the other responsibilities we know you have.
I hope that after watching this video you recognize the great resources you have at your fingertips. It is our hope that by supplying you with this information, you come into this course confident in your ability to do well.
I would like to touch on two other pivotal resources you have at your disposal. The first is your instructor. Even though you're not in the same room, you can email, call, or talk to them during online office hours. Secondly, you have me, your Student Success Coordinator. Think of me as your catch-all. Any questions, comments, concerns that you have, please feel free to reach out to me via email, text, or phone call. I will assist with keeping you on track to graduation and share your program plan pathway with you. I'm here to support you from the day you join the program to the day you get your diploma.
Thank you for listening, and I look forward to supporting you in the future.
Introduction to the Interface
In this brief video, Student Success Coordinator Jac Cooper walks you through basic navigation of the course demo for the Online MSBA program’s Machine Learning for Business course.
Experience It for Yourself
The organization and layout of all Seattle U’s Albers School of Business online courses are similar to this demo. Our robust and user-friendly online portal helps you organize all your materials and makes interacting with your professors and classmates easy.
Online R and Python Programming Prep Course
All new students in the Online MSBA program are required to complete a prep course in the R and Python programming languages prior to the beginning of their first term. This six-hour course will be offered online and may be completed before or during your New Online Student Orientation.
Designed for those with or without coding experience, the course helps students develop the beginner skills and experience needed so they are fully prepared for their MSBA coursework. During the prep course, students will:
- Install Python and R on their machines
- Familiarize themselves with basic syntax
- Learn basic programming in Python and R
OMSBA 5112 Statistics for Business Analytics (3 credits)
OMSBA 5061 Programming I for Business (3 credits)
OMSBA 5280 Law and Ethics for Business Analytics (3 credits)
This course will examine the opportunities and challenges introduced by business analytics through the perspectives of the law and ethics. Rapidly evolving technologies that permit the collection, storage, aggregation, analysis, and use of data create opportunities for financial benefit and the common good, but also create challenges to legal rights such as privacy, equality, and dignity, and to ethical values such as autonomy, trust, and virtue. The course will be framed as a contextual examination of business analytics to facilitate learning about legal and ethical standards for private organizations using data analytics techniques in various stages of the data life cycle. This is a dynamic course which presents a rich basis for student learning and contemplation of central questions for “big data,” including issues related to acquisition and use of data, professional and social responsibility in the application of modern technologies, the efficacy of management by algorithm, and the loss of human control in using artificial intelligence. The following are examples of legal and ethical issues that may be included, subject to time constraints: In law: information privacy law such as U.S. tort law, federal statutory and administrative law, and constitutional protection of civil liberties; European Union data privacy regulation; cyber intelligence and cybersecurity regulation; contractual liability, specifically with respect to third-party reliance on data analysis; the law of negligence; and agency law. In ethics: adverse effects of data collection on vulnerable populations; transparency and honesty in the cleaning, processing, and visualization of data; introduction of the machine equivalent of implicit bias in feature selection; and responsibilities when using data analysis as a tool to guide human decision-making. Registration restrictions may be bypassed by the department with permission of instructor.
OMSBA 5210 Data Wrangling, Visualization, and Communication (3 credits)
Learn the essential and practical skills necessary to communicate information about data clearly and effectively through written, oral, and graphical means. Students will learn and practice with advanced visualization tools to effectively communicate. The course will build from the understanding of data to the presentation of the analysis. Data visualization “storytelling" will provide tools to effectively: communicate ideas, summarize, influence, explain, persuade, and provide evidence to an audience. Visualization can convey patterns, meaning, and results extracted from: multivariate, geospatial, textual, temporal, hierarchical, and network data. During the course, students will deliver presentations using these techniques, and they will also learn to critically evaluate other presentations.
OMSBA 5062 Programming II for Business (3 credits)
OMSBA 5305 Economics and Business Forecasting (3 credits)
OMSBA 5240 Enhancing Stakeholder Relationships in the Age of Analytics (3 credits)
OMSBA 5270 Analytics for Financial Decisions and Market Insights (3 credits)
OMSBA 5315 Big Data Analytics (3 credits)
OMSBA 5145 Database Management (6 credits)
The first half of the course is focused on the relational model and SQL queries, using Microsoft SQL Server for practice and assignments.
The second half of the course dives into the data management concepts of MongoDB and Hadoop, respectively, and provides an opportunity for students to query data structures that are distinctly different from the traditional SQL relational databases.
OMSBA 5300 Applied Econometrics (3 credits)
OMSBA 5068 Artificial Intelligence for Business (3 credits)
OMSBA 5067 Machine Learning (6 credits)
This course explores fundamental concepts for developing machine-learning models to solve business problems by analyzing massive amounts of data to find interesting patterns that can be used to assist decision making or provide predictions. Topics covered include regression, decision trees, clustering algorithms, naïve Bayes classification, evaluation metrics, model refinement, ensemble methods, neural networks and deep learning, dimensionality reduction, and association rule mining. Students are expected to analyze real-world data in business using machine learning tools.
Prerequisite: C or better in OMSBA 5061 (Programming I) and OMSBA 5112 (Applied Statistics)