Center for Business Analytics to offer generative AI course in June
Limited seats available for virtual two-day training
The University of Cincinnati Center for Business Analytics at the Carl H. Lindner College of Business will host a generative artificial intelligence (AI) course June 3 and June 5.
The center is offering “Generative AI in Business: Applications, Challenges, Ethics and Governance,” a first-of-its-kind course, in response to interest from the community and increasing demand in the marketplace, with no prior experience required to participate.
Mike Fry, PhD, professor of operations, business analytics, and information systems and managing director of the Center for Business Analytics.
Generative AI is still new and evolving quickly, which presents challenges for organizations of all sizes that are curious but don’t yet have the knowledge or resources to determine what specific use cases, approaches and tools can help them gain a competitive edge in their industry.
“Generative AI offers possibilities for the business community in everything from content generation to personalization of products and services, to efficiency gains to improved customer service experiences, to enhanced analytics capabilities,” said Mike Fry, managing director for the Center for Business Analytics and professor of operations, business analytics, and information systems.
The course will be delivered virtually in two three-and-a-half-hour sessions. Assistant Professor-Educator and Joseph S. Stern Professorship of Practice Jeffrey Shaffer will serve as the live instructor, with graduate assistants available for technical support for attendees.
Jeffrey Shaffer will serve as the live instructor for the virtual two-day workshop "Generative AI in Business: Applications, Challenges, Ethics and Governance" June 3 and 5.
"From basics to breakthroughs, our live virtual sessions are designed to demystify the complexities of AI and equip attendees with hands-on skills,” said Shaffer. “This workshop offered through our Center for Business Analytics will be a gateway for understanding and applying generative AI for our attendees, empowering them with actionable insights and practical techniques that can drive innovation in their field.”
Since no prior experience is required to participate, course content starts with fundamental concepts of generative models, such as GPT, BERT and diffusion. Attendees will then advance into understanding model capabilities in various domains including translation, classification, text and image generation, and more. Additionally, the course will cover critical discussions on the governance and ethics of generative AI systems, addressing the societal, ethical and regulatory implications of these technologies.
- Introduction to Generative AI
- Understanding generative AI (GenAI)
- Evolution of AI models
- Overview of generative pretrained transformers (GPT) and their impact
- Foundational Concepts
- Transformer models: Encoder, decoder and attention mechanisms
- Difference between models: BERT vs. GPT
- Introduction to tokenization
- Vector Databases
- Generative AI Applications
- Text generation
- Summarization
- Translation and classification
- AI in creative arts: From text to images
- Advanced Models and Platforms
- Overview of current generative AI models (ChatGPT, GPT-4, Claude 3, Llama2, Bard/PaLM 2, etc.)
- Introduction to Hugging Face and the Open LLM Leaderboard
- Comparative analysis of GenAI platforms
- Prompt Engineering and Applications
- Zero-shot and few-shot learning
- Chain-of-thought (CoT) prompting and tree of thoughts (ToT)
- Role-based and temperature settings in AI prompts
- Governance and Ethics of Generative AI Systems
- Understanding the ethical implications of GenAI
- Governance frameworks for AI
- Privacy, bias and fairness in AI models
- Regulatory and societal impacts
- Case studies on ethical dilemmas
- Demonstrations and Hands-on Sessions
- Utilizing OpenAI's ChatGPT & Playground for advanced data analysis
- Integrating GenAI in workflow (Copilot - Excel, Word, PowerPoint)
- Building custom GPT models for specific tasks
- Business Use-Case Examples
- Discussion and demonstration of projects that apply generative AI techniques to real-world data analytics problems
- Practical implications of GenAI technologies
- Conclusion and Future Directions
- Reflection on the potentials and limitations of GenAI
- Discussion on the future trends in AI technologies
A certificate of completion will be provided at the end of the workshop describing six instruction hours for the field of study “information technology”, equivalent to 0.8 continuing education units (CEUs).
Registration is limited and going fast. Secure your spot by registering today.
Featured image at top courtesy of Adobe Stock.
About the UC Center for Business Analytics
The Center for Business Analytics unites organizations and a world-class, multidisciplinary group of faculty and students to educate and exchange ideas and best practices on applying analytical methods to enhance business performance. To inquire about membership, sponsorship, training or speaking opportunities, email UCBusAnalytics@ucmail.uc.edu.
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