Concurrent Session #4: Building Process Bots: Automate Custom AI Processes Using Low-Code/ No-Code Tools

Alternative Title

Building Process Bots: Automate Custom Artificial Intelligence (AI) Processes Using Low-Code/ No-Code Tools

Contributor

University of Central Florida. Faculty Center for Teaching and Learning; University of Central Florida. Division of Digital Learning; Teaching and Learning with AI Conference (2023 : Orlando, Fla.)

Location

Cape Florida A

Start Date

24-9-2023 2:45 PM

End Date

24-9-2023 3:00 PM

Publisher

University of Central Florida Libraries

Keywords:

Low-code; No-code; AI workflows; Automation; OpenAI API

Subjects

Automation--Data processing; Artificial intelligence--Educational applications; Automation--Study and teaching; Research--Automation; Artificial intelligence--Computer-assisted instruction

Description

Use low code/no code applications to create your own custom applications for automating AI workflows. In using the two main tools of Zapier, a no-code application connection tool, and an OpenAI API key you can create your own custom automated workflows by pulling together various web applications and sending that to LLM processing. For example, how does one automatically create AI-generated knowledge-check quizzes for every lecture video posted in a course? This custom application approach takes the time-saving usage of AI for language processing to another level of automated efficiency.

Language

eng

Type

Presentation

Rights Statement

All Rights Reserved

Audience

Faculty, Instructional designers

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Sep 24th, 2:45 PM Sep 24th, 3:00 PM

Concurrent Session #4: Building Process Bots: Automate Custom AI Processes Using Low-Code/ No-Code Tools

Cape Florida A

Use low code/no code applications to create your own custom applications for automating AI workflows. In using the two main tools of Zapier, a no-code application connection tool, and an OpenAI API key you can create your own custom automated workflows by pulling together various web applications and sending that to LLM processing. For example, how does one automatically create AI-generated knowledge-check quizzes for every lecture video posted in a course? This custom application approach takes the time-saving usage of AI for language processing to another level of automated efficiency.

Accessibility Statement

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