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AI Seminars

We offer short training seminars on applied AI methods and LLM workflows that are becoming essential for research, analytics, and data-intensive work across academia and industry.

Cutting-edge. Hands-on. Complete.

Public Seminars

AI Horizons offers public AI and LLM training seminars. We help participants and clients build a strong foundation in LLM workflows (using tools like ChatGPT, Claude, and Gemini), prompting strategies, and AI-assisted approaches that can be applied with confidence in real projects.

Looking for customized training for your organization? See our onsite AI seminar options.

Public Seminars

Each course features small group sizes, top-notch instructors, and extensive hands-on practice. Participants will use their own laptop computers, pre-loaded with relevant software and datasets provided prior to the beginning of the seminar.

Our upcoming seminars are listed below—click a course title for details and registration. All courses are livestreamed via Zoom. Video recordings are available to participants for an additional four weeks after the seminar ends.

Certification pathways are available as well.

Multilevel and Mixed Models Using R and LLMs

September 16-18, 2026

In addition to providing a solid foundation in using mixed models in R, this course will also equip you with a set of structured prompts to use with your large language model (LLM) of choice.

Instructor: Stephen Vaisey

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AI Agents for Teaching

September 24-26, 2026

Explore how AI agents can be used to improve teaching, strengthen assessment, and create more engaging learning environments.

Instructor: Charles Crabtree

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Text Classification with LLMs in R

October 7-9, 2026

Learn to use natural language processing (NLP) techniques and large language transformer models (LLMs) for research applications using R.

Instructor: Hudson Golino

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Getting Work Done with AI Agents

October 21-23, 2026

Discover how to use AI agents as research collaborators by building agent-ready workspaces, project memory systems, and repeatable workflows.

Instructor: Mitchell Bosley

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Python for R Users with AI Assistance

October 22-23, 2026

Apply your existing R experience to build practical Python skills, using AI coding assistants to translate code, troubleshoot errors, and develop workflows for data analysis, visualization, and basic machine learning.

Instructor: Adam D. Rennhoff

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AI Tools for Data Analysis: From Chatbots to Coworkers

October 29-30, 2026

Explore how to use AI tools and coding agents to clean and analyze data, create visualizations and dashboards, automate workflows, and verify outputs for more reliable, shareable results.

Instructor: Boris Nikolaev

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AI-Based Emotion Analysis for Text, Image, and Video

November 4-6, 2026

Analyze emotions and sentiment across text, images, and video using transformer AI models in R, while learning to score, evaluate, and report multimodal results transparently.

Instructor: Hudson Golino, Aleksandar Tomašević

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Claude-Powered Academic Research: From Ideation to Publication

November 19-21, 2026

Learn how to use Claude as a systematic research partner for ideation, data collection, analysis, reproducibility, and publication-ready academic writing.

Instructor: Jeffrey Dotson

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LLM Agents for Research Using R

December 2-4, 2026

Build custom AI research agents in R that can search, retrieve, analyze, and verify information to support literature reviews, research design, and more.

Instructor: Hudson Golino

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R for SPSS Users with LLM Applications

December 9-11, 2026

Learn how to translate SPSS workflows into R code while using LLMs to debug, improve analyses and visualizations, convert syntax, and navigate common coding challenges.

Instructor: Christopher L. Aberson

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AI Agent-Driven Research Workflows

January 20-22, 2027

Learn structured, practical ways to coordinate AI agents and tools across multistep research workflows, reducing low-value work while maintaining oversight and avoiding hidden errors.

Instructor: Charles Crabtree

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Advanced Machine Learning and Applied AI Workflows

February 24-26, 2027

Go beyond basic machine learning techniques and deepen your ability to handle complex data challenges while building practical, end-to-end AI workflows.

Instructor: Bruce Desmarais

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