Tabulate a query:
In[140]:=
LLMResourceFunction["WolframUDataScienceBootCampBot"]["Which sessions specifically discuss LLMs? Give the results as a Markdown table."]//ResourceFunction["ImportMarkdownString"]
Out[140]=
Certainly! Here is a Markdown table listing the sessions that specifically discuss LLMs (Large Language Models) in the Wolfram U Data Science Boot Camp syllabus: ​
Day & Date
Time
Session Title
Instructor(s)
Description/Focus
Day 5 (Fri, Aug 8)
9–11:30am
Programming with LLM Functions
Jon McLoone
Introduction to using LLM functions in Wolfram Language.
Day 5 (Fri, Aug 8)
1–3pm
Hands-on Explorations for LLM Functions
Arben Kalziqi, Mike Yeh
Practical exercises integrating LLMs with Wolfram Language for text and data analysis.
Day 9 (Thu, Aug 14)
10:15–11:30am
Case Study: Running Local Large Language Models and Integrating with Databases
Jofre Espigule-Pons
Running LLMs locally, developing custom prompts, and integrating with databases in Wolfram Language.
Day 9 (Thu, Aug 14)
1–2:30pm
Case Study: Making Robust LLM Computational Pipelines from SE Perspective
Anton Antonov
Methodological approaches to robust software engineering pipelines that include LLMs.
Day 10 (Fri, Aug 15)
9–10am
Closing Keynote: Harnessing the Synergy of LLMs and Wolfram Language
Marco Thiel
Integrating LLMs with Wolfram Language for industrial-grade data science solutions.
​Let me know if you need more details about any of these sessions, DS/Bot.

Scope 
(1)
 

The prompt is an LLM persona (not an LLM function.) Hence it is better to use with
LLMSynthesize
and
LLMPrompt
:
In[145]:=
query="What talks are on going on in August 14th? Tabulate the result as dataset";​​LLMSynthesize[{LLMPrompt["WolframUDataScienceBootCampBot"],query,LLMPrompt["NothingElse"]["Wolfram Language"]}]//ToExpression
Out[146]=