AI in Your Research: Workshop Offerings
TDAI’s hands-on AI in Your Research workshop series for OSU researchers is designed to help academic researchers integrate cutting-edge AI tools into their scholarly work. Whether you're just beginning to explore AI or looking to deepen your technical fluency, this series provides practical, discipline-spanning guidance tailored to a range of experience levels.
Aimed at building AI fluency across the research enterprise, this series is central to TDAI’s mission to advance big data-enabled research and innovation at Ohio State. Due to strong interest, the series is expanding with new sessions and will continue to grow into a full slate of offerings through 2026. Consulting services are also available upon request.
Upcoming Workshops
Workshops are offered individually — register for one, two, or all three. Each session runs over two days from 9:00 AM – 3:00 PM.
Generative AI in Your Research
May 20–21, 2025
Build LLM-powered literature review tools in Python
🔗 https://tdai.osu.edu/events/summer-workshop-series-generative-ai-your-research
Machine Learning in Your Research
May 27–28, 2025
Build predictive and interpretable models in Python
🔗 https://tdai.osu.edu/events/summer-workshop-series-machine-learning-your-research
Computer Vision in Your Research
June 3–4, 2025
Build image analysis workflows in Python
🔗 https://tdai.osu.edu/events/summer-workshop-series-computer-vision-your-research
🔗 Register here:
https://osu.az1.qualtrics.com/jfe/form/SV_51kbrJK2pT98n2e
Cost: $260 per workshop ($130 for students)
Payment accepted via credit card, purchase order, or requisition
Workshop Offerings
Workshop Offerings
Generative AI in Your Research
An interactive, application-focused workshop that introduces the use of Large Language Models (LLMs) in research. Participants will build tools to enhance and streamline the academic literature review process while working hands-on in Python.
Key topics include:
- Transformer architecture and how modern LLMs work
- Commercial and open-source LLM options
- Prompt engineering best practices
- Ethical and security considerations
- Document processing for LLM workflows
- Retrieval-Augmented Generation (RAG)
- Techniques for summarizing literature and identifying research connections
Machine Learning in Your Research
This workshop covers the foundations and practical application of machine learning methods for research. Participants will build predictive and interpretable models using real-world datasets in Python.
Key topics include:
- Supervised and unsupervised learning concepts
- Model selection and when to use different approaches
- Data preprocessing and feature engineering
- Model evaluation and avoiding overfitting
- Interpreting model outputs and feature importance
- End-to-end machine learning workflows
Computer Vision in Your Research
This workshop introduces methods for analyzing and extracting insights from image data. Participants will develop practical computer vision workflows in Python applicable across research domains.
Key topics include:
- Fundamentals of image data and representation
- Classical computer vision and deep learning approaches
- Image preprocessing and augmentation
- Feature extraction and pattern recognition
- Applying computer vision techniques to research use cases