Get ready for an inspiring two semesters
Build a solid foundation in advanced business analytics techniques while exploring your interests through electives and experiential learning opportunities. Spend a semester solving a real business problem for a real company in the Analytics Experience course. Choose your track to show future employers exactly the kind of role you'd like to pursue and exactly how your skills align with it.
Core courses
Courses you'll take vary slightly based on the track you choose.
Advanced Analytics (BAIS:9110)
- How did the 2001 terrorist attacks impact travel patterns and behavior in the United States? Determine hypothetical trends if the attacks had not happened using time series analysis.
- How can I create an index fund to track a particular financial sector? Solve an optimization model to choose a representative sample of companies in which to invest.
- How do companies use analytics? Present a case study of a large company using analytics successfully.
Advance Technical Communication (BAIS:7120)
Developing readiness for interacting with clients including status reports, balancing technicality based on audience, and delivering a presentation to an external audience about a finished work product.
Analytics Experience (BAIS:6120)
Students work in groups on a semester-long project focused on business analytics. The project covers all stages, including problem definition, data cleaning, analysis, and the final presentation. Throughout the project, students will apply tools and techniques learned from previous courses.
Applied Deep Learning (BAIS:6250)
Explore generative models & associated data mining techniques.
Pre-req - BAIS:6260 Generative AI pre-req BAIS:9100 and BAIS:6040 and BAIS:6070 and co-req BAIS:6250
Data Management (BAIS:6050)
- Companies have troves of data – from customer spending habits to financial forecasts to investment trends. How is this information stored in databases and what tools are used to create data sets?
- Vast amounts of data can be complex to store and manage. Is there a way to use Structured Query Language (SQL) to manage and access data in relational databases?
- What are the best ways to present data retrieved from databases?
Data Programming in Python (BAIS:6040)
- How can I use the Python programming language to understand the principles and practices of handling, cleaning, processing, and visualizing data?
- What basic data programming skills do I need to understand and work with data types, control structures, functions and modules, and other useful libraries for data manipulation and machine learning applications?
Data Science (BAIS:6070)
- Will this stock price go up or down tomorrow? What about in the next 5 seconds? Identify opportunities for profitable trades.
- Which of these people is most likely to respond to a direct marketing contact? Segment your customers for better targeting, and identify the most promising new leads.
- What kind of approach might move a donor to a higher giving level? Conduct a design of experiments to gather the most information from your trial marketing campaign.
Managerial Communication (BAIS:7110)
Effective communication to become a successful business professional and leader; strengthen ability to speak and write confidently, competently, and effectively regardless of venue; varied team and individual presentation coaching, applied exercises.
Professional Development and Business Acumen (BAIS:9400)
- Professional success often comes down to connections. After I graduate, and maybe before, how do I grow a professional network?
- Who can I turn to and what sources do I need to stay up to date on current trends and activities in business analytics?
- I’ve decided on a career in business analytics. What are some best practices and who can I turn to for guidance?
Required in two semesters (1 s.h. each semester)
Visual Analytics (BAIS:6140)
- We’re surrounded by data. How do we effectively interpret and communicate that information?
- When presenting data findings to a diverse group, how do I use the theoretical foundations of visual perception to communicate in a way that anyone can understand?
- What are the best tools to effectively show data findings in charts, graphs, or other visual ways? We’ll explore Tableau, Power BI, and others.
Requirements for each track
Artificial Intelligence and Machine Learning
Text Analytics (BAIS:6100)
- Turning lead into gold. How can I convert unstructured emails, tweets, blogs, customer reviews, etc. into insights?
- How do I identify relevant sources, harvest the data, manage large databases, and use techniques to change words into quantifiable metrics?
Social Analytics (BAIS:6105)
- Digital interactions become more business-critical by the day. What are the best practices for the collection, management, and analysis of social data?
Generative AI (BAIS:6260)
Introduction to basics of generative artificial intelligence (AI) models and their practical applications.
Key concepts include modal representation and generative models, scalability aspects of these models, and implementation techniques such as pre-training, fine-tuning, and prompt engineering.
Emphasizes hands-on skills, including how to work with pre-trained models, evaluate performance, and ensure alignment with goals. Business case studies will help students apply AI responsibly and set realistic expectations for its use. Ethical issues, privacy concerns, and the regulatory landscape will be discussed to prepare students for challenges of using AI in real-world settings.
Artificial Intelligence Technology Management
Data Management and Leadership (BAIS:6210)
- How do I manage a team of analytics and IT professionals?
- What are the best practices for a CIO (chief information officer) or other data manager?
Agile Project Management (BAIS:9140)
- How do I create or participate in a successful agile work environment?
- What are various agile methods like scrum, lean, Kanban, and XP?
- Learn to apply story mapping, advanced planning and estimating, and scaling methods.
Value Creation Using Artificial Intelligence (BAIS:6240)
- Gain a comprehensive understanding of how artificial intelligence (AI) can be harnessed to create value in various business sectors including AI fundamentals; frameworks for value creation.
- What are competitive strategies using AI, the critical success factors for AI-based projects, and use cases for a various industries?
- Are there ethical considerations of privacy, trust, and security issues related to AI?
Finance Analytics
Text Analytics (BAIS:6100)
- Turning lead into gold. How can I convert unstructured emails, tweets, blogs, customer reviews, etc. into insights?
- How do I identify relevant sources, harvest the data, manage large databases, and use techniques to change words into quantifiable metrics?
Managerial Finance (MBA:8180)
Finance majors with a minimum 3.3 major GPA or with CFA level 1.
Corporate Investment and Financing Decisions (FIN:9300)
- Learn the underpinnings and optimization of corporations’ investment and financing decisions.
- How do I consider firm-wide and project-specific cost of capital, optimal capital structure decisions, conduct in-depth capital budgeting methods, including real options techniques?
- The corporate investment module of the class includes simulation analysis using Crystal Ball; cost of capital, valuation techniques, advanced capital budgeting, capital structure and dividend policy.
- Prerequisites: MBA:8180.
Summer pre-work requirement for incoming Business Analytics students
All admitted Business Analytics students are expected to complete a required online summer pre-work experience. This foundational work is designed to ensure that all students begin the program with the necessary baseline knowledge to succeed.
The process begins with a pre-assessment. Students who meet the required proficiency on this initial test will not need to complete any further summer work.
For those who do not test out, there will be nine required online modules, each ending with a quiz. These modules are self-paced and asynchronous, and students can attempt the quizzes as many times as needed. Each module is estimated to take approximately 140–165 minutes to complete.
Once all modules are completed, students will take a final post-assessment, with up to two attempts allowed.
Please note: Students who do not complete the required summer pre-work (either by testing out or completing all modules and passing the post-assessment) will extend their time to degree completion from two semesters to four semesters.
This required pre-work is free, fully online, and can be completed on your own schedule during the summer months.
Communication matters to employers—and to us
At the top of every hiring manager's list: data-savvy professionals who can work the numbers to draw conclusions and clearly communicate their results. Our employer partners tell us that most analysts fall far short in this regard.
We target this skill gap with a unique model: pairing a Business Communication course with a technical course every Spring semester. In the Fall, the Business Communication course will be a stand-alone. By the end of semester two, you'll be able to clearly show that you can understand business problems, solve them with data, and communicate to the people who matter.
“The business world needs people with technical skills who can also communicate in a clear and concise way. Tippie does a great job of providing both.”
Sample plan of study
The full-time Master of Business Analytics plan of study spans two semesters, including core and sub-program courses.
Summer |
|---|
| Pre-Work: Data and Decisions Bootcamp |
Fall 2nd 8 Weeks | 17sh | |
|---|---|---|
| BAIS:6040 Data Programming in Python | Track course | 6 |
| BAIS:6050 Data Management |
| 3 |
| BAIS:6070 Data Science |
| 3 |
| BAIS:9110 Advanced Analytics |
| 3 |
| BAIS:9400 Professional Development Business Acumen | BAIS:7110 Managerial Communication | 2 |
Spring 1st 8 Weeks | Spring 2nd 8 Weeks | 16sh |
|---|---|---|
| BAIS:6140 Visual Analytics |
| 3 |
| BAIS:6250 Applied Deep Learning |
| 3 |
| BAIS:6120 Analytics Experience |
| 3 |
| BAIS:7120 Advance Technical Communication |
| 1 |
| Subprogram Course | Track Course | 6 |
Total: | 33 |
Artificial Intelligence & Machine Learning Subprogram - 9sh
| Course | Prerequisites | Semester |
|---|---|---|
| BAIS:6100 Text Analytics | BAIS:6040 Co-req - BAIS:6070 | Fall 2nd |
| BAIS:6105 Social Analytics | BAIS:6040 & 6070 | Spring 1st |
| BAIS:6260 Generative AI | BAIS:6040 & 6070 Co-req - BAIS:6250 | Spring 2nd |
Artificial Intelligence Technology Management Subprogram - 9sh
| Course | Prerequisites | Semester |
|---|---|---|
| BAIS:6210 Data Management & Leadership | None | Fall 2nd |
| BAIS:9140 Agile Project Management | None | Spring 1st |
| BAIS:6240 Value Creation Using AI | None | Spring 2nd |
Finance Analytics Subprogram - 9sh
| Course | Prerequisites | Semester |
|---|---|---|
| BAIS:6100 Text Analytics | BAIS:6040 | Fall 2nd |
| MBA:8180 Managerial Finance | Spring 1st | |
| FIN:9300 Corporate Investment & Finance Decisions | MBA:8180 | Spring 2nd |