Duke provides a variety of opportunities to explore, learn, and create with AI. Whether you’re experimenting independently, seeking expert guidance, or pursuing support for a larger initiative, this page will help you identify the resources and pathways that best meet your goals.
Self-Guided Training
Below is a sample of online courses and videos that provide an introduction to generative AI.
This introductory course is designed for beginners with no prior knowledge of generative AI. You will start by gaining a high-level understanding of what generative AI is and how it works. Through interactive lessons and hands-on examples, you will learn fundamental skills like providing effective prompts and iteratively improving the generated outputs. As the course progresses, you will dive deeper into specific major generative AI models, including their unique capabilities and limitations. Finally, you will get practical experience using leading systems like GitHub Copilot, DALL-E, and OpenAI to generate code, images, and text. By the end, you will have developed core knowledge to start experimenting with generative AI in a responsible and effective way for a variety of applications. This course aims to provide a friendly introduction to prepare complete beginners for further exploration of this rapidly evolving technology.
This 15-minuute video introduces ChatGPT features including interface, custom settings, project management, model selection and lecture notes/citations.
This course introduces students to the patterns and approaches for writing effective prompts for large language models. Anyone can take the course and the only required knowledge is basic computer usage skills, such as using a browser and accessing ChatGPT. Students will start with basic prompts and build towards writing sophisticated prompts to solve problems in any domain. By the end of the course, students will have strong prompt engineering skills and be capable of using large language models for a wide range of tasks in their job, business, personal life, and education, such as writing, summarization, game play, planning, simulation, and programming.
The course will show you how to:
- Leverage prompt engineering techniques to generate more reliable outputs
- Master methods to verify and validate outputs
- Frame problems in alternative ways to reduce risk
- Apply generative AI for creative ideation
- Use Generative AI in ways that augment rather than replace human reasoning and creativity
Learn how AI can break down complex topics, support structured thinking, deep research, essay outlines and other study aids.
Throughout this series, learners will explore key topics including Explainable AI (XAI) concepts, interpretable machine learning, and advanced explainability techniques for large language models (LLMs) and generative computer vision models. Hands-on programming labs, using Python to implement local and global explainability techniques, and case studies offer practical learning. This series is ideal for professionals with a basic to intermediate understanding of machine learning concepts like supervised learning and neural networks.
This 17- minute video demonstrates how AI can automate and organize tasks and how to build a GPT.
Need Additional Support with AI?
- Attend a Roots program workshop
- Access the Academic Resource Center AI toolkit
- Visit the Innovation Co-Lab's AI-focused blog, In The Loop
- Join the Duke AI Suite User Group on Microsoft Teams for peer-to-peer support
- Check out Duke’s AI Suite quick links document
- Email dukectl@duke.edu to schedule time with one of our Teaching Consultants
- Consider an AI consultation
- For tech support, submit a ticket to the OIT Service Desk