Event Phone: 1-610-715-0115

Cancellation Policy: If you cancel your registration two weeks or more before the course is scheduled to begin, you are entitled to receive your choice of either a credit for a future seminar (which can be applied toward any of our courses) or a refund of the registration fee (minus a processing fee of $50). 

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

An 8-Hour Livestream Seminar Taught by Hudson Golino, Ph.D.

This seminar is part of our AI-Enabled Data Analytics Certification Program, a series of 4 expert-led courses designed to build practical AI skills for research and data analysis. Contact us to learn how to complete your certification and access special pricing.

Have you ever wondered how to generate text data (for example new items) automatically for your research project (survey, questionnaire) using AI? Are you interested in having more control over the output of ChatGPT responses (or other LLMs)? Do you want to verify the impact of different prompting engineering techniques on the quality of the items or text data you create with the Large Language Models? If so, this course is for you.

This intensive two-day workshop is designed to provide you with a comprehensive introduction to text generation via LLMs (OpenAI Models: GPT-3.5-TURBO/GPT-4, GPT-4o, the open source OpenAI models GPT-OSS-120b, GPT-OSS-20b, plus other open source models such as Llama-3.3, Llama-4, and others), with a specific focus on how to use them in the R programming environment using APIs (OpenAI and Groq Cloud Systems).

Whether you are a beginner or an experienced data scientist, this course will equip you with the skills and knowledge needed to harness the full potential of the LLMs for text generation, including advanced prompt engineering techniques and API control methods.

By the end of this course, you will be able to:

• Set up and configure LLM APIs (OpenAI and Groq) within the R environment.
• Apply advanced prompt engineering techniques including role prompting, few-shot learning, chain-of-prompting, and chain-of-thought reasoning.
• Generate high-quality survey items and research materials grounded in psychological theory.
• Extract key concepts from research papers (PDFs) to inform item or text development.
• Implement prompt chaining for complex, multi-step analysis tasks.
• Create automated pipelines for large-scale text generation and analysis.
• Minimize hallucinations through evidence-based grounding techniques.