Artificial Intelligence in Business
In the past several years, artificial intelligence (AI) has fundamentally changed the way humans are able to gather and process information. Based on input from employers, alumni and our advisory board, we believe artificial intelligence literacy will become a key differentiating factor for future analytics professionals.
Because of this, we have made AI a key component of the Carlson School Master of Science in Business Analytics curriculum. Here, you’ll learn AI-related tools and techniques to help differentiate yourself in the job market.
How AI is infused into the MSBA curriculum
Even before the release of ChatGPT, we have steadily increased coverage of AI in our curriculum. To further enhance these efforts, the MSBA curriculum has been redesigned to place an even larger emphasis on AI. Throughout your three semesters in the program (fall, spring and summer), you will be exposed to critical AI topics. Starting in fall 2024:
- Exploratory Data Analytics (2nd semester - spring)
- Predictive Analytics (2nd semester)
- Responsible AI (3rd semester - summer)
- Time Series Analysis and Forecasting (3rd semester)
- Generative AI for Business Applications (2nd semester)*
- Advanced AI for Natural Language Understanding (3rd semester)*
- Recommender Systems Techniques and Applications (3rd semester)
*Required for the AI for Business track
AI for Business track
While all MSBA students will learn foundational AI topics, you can choose to take additional courses to become even more skilled in this area. To complete the AI for Business track, you must take these two elective courses:
- Generative AI for Business Applications (2nd semester)
- Advanced AI for Natural Language Understanding (3rd semester)
AI topics covered
Multiple MSBA courses introduce the key models and algorithms behind AI applications and their business applications to help you build your skills in this area.
|Required or Elective
|AI Topics Covered (may vary each semester)
|MSBA 6411: Exploratory Data Analytics
|Autoencoder, large language models for explorative analytics
|MSBA 6421: Predictive Analytics
|Deep Neural Network, Convolutional Neural Network (CNN), Recurrent Neural Network (RNN)
|MSBA 6155: Generative AI for Business Applications
|Applications, limitations, ethical and social implications of generative AI, ChatGPT, Midjourney
|MSBA 6141: Responsible AI
|Explainable AI techniques, privacy-preserving AI techniques, fairness-aware machine learning models
|MSBA 6351: Time Series Analysis and Forecasting
|Use of deep-learning-based models such as deep autoregressive models, Long Short-Term Memory (LSTM), and transformers for forecasting
|MSBA 6431: Recommender System Techniques and Applications
|Context-aware and deep-learning empowered recommender systems, including neural collaborative filtering, deep factorization machine, and self-attentive sequential recommendation
|MSBA 6461: Advanced AI for Natural Language Understanding
|Natural language processing, recurrent neural networks (RNN) such as Long Short-Term Memory (LSTM), gated recurrent unit (GRU), etc., sequence-to-sequence model, attention mechanism, transformer architecture
Why AI is important for business analytics students
Our goal is to equip you with the skills and knowledge needed to succeed in business analytics roles after graduation.
Based on insights gathered from employer surveys, alumni feedback, and our advisory board, we have identified a growing demand for data professionals proficient in training and deploying AI models and utilizing generative AI tools. These skills are highly coveted in the current marketplace. The extensive AI coverage in our curriculum will enable you to develop a good understanding of these technologies and the ability to harness them responsibly and effectively to create value for businesses.
No matter how much you choose to focus on AI when you’re in the MSBA program, you will gain valuable analytics skills and business acumen that will enhance your career prospects.
Frequently asked questions
No. The required courses in the MSBA curriculum build a solid foundation to understand advanced AI techniques.
Our Responsible AI course is designed exactly for this purpose. This course covers various ethical considerations of AI (e.g., algorithmic bias, privacy issues, AI security, and AI transparency). The course has hands-on components so you not only learn about the concepts but also specific techniques you can employ to build responsible AI systems and solutions.
No. You can take elective courses that do not focus on AI. However, AI will still be a core component of some required courses given how important it is in the industry today.
The full extent of the impact of AI on all industries is yet to be seen. A general consensus seems to be that generative AI is a productivity boosting tool, including boosting the productivity of data scientists and data engineers. AI hasn’t eliminated the role of data scientists/engineers; rather, it has enhanced their capabilities and reduced the time spent on repetitive tasks. Our belief is that the industry needs data science professionals who can understand and effectively leverage generative AI.