AI Fluency in the Education Space
Training Provider: SINGAPORE UNIVERSITY OF TECHNOLOGY AND DESIGN
Course Reference: TGS-2025060995
S$750
Original: S$2,500
Save S$1,750
About This Course
This 2-day course is designed to increase Artificial Intelligence (AI) fluency in the education space, with emphasis on grading systems, generative AI creative tools, and adaptive learning platforms. The course is modular in structure that address areas of pedagogical fundamental interest, such as, ethical implications of AI use, foundational concepts of AI architectures that power modern AI, increase productivity as educators using OpenAI Large Language Model (LLM) models, AI tools for rapid video creation, chatbots and practical zero-code strategies to integrate AI into teaching practice and curriculum design to support grading, feedback, and general learning guidance.
What You'll Learn
a. Address evaluation of assignments that use Artificial Intelligence (AI) for any ethical deviations
b. Identify ethical concerns in AI use to create an ethical framework to apply to AI solutions
c. Distinguish between core AI architectures, such as, neural networks, U-net (diffusion), and attention mechanisms
d. Understand, and execute, the training process of AI models using labelled datasets.
e. Use free and paid AI tools to use minimum efforts to produce instructional videos.
f. Use ChatGPT to generate and modify Python codes to create an Large Language Model (LLM)-based education tools.
g. Incorporate rubrics for assessments through Application Programming Interface (API).
h. Read and write spreadsheet data with vibe coding and compile grade computions from learning management systems (LMS).
i. Guide learners in using GPT-based tools for ideation, iteration, and reflection in design thinking.
j. Identify when a course-specific chatbot offers more value than a generic AI chatbot.
k. Develop and deploy a chatbot as a standalone link or frame.
b. Identify ethical concerns in AI use to create an ethical framework to apply to AI solutions
c. Distinguish between core AI architectures, such as, neural networks, U-net (diffusion), and attention mechanisms
d. Understand, and execute, the training process of AI models using labelled datasets.
e. Use free and paid AI tools to use minimum efforts to produce instructional videos.
f. Use ChatGPT to generate and modify Python codes to create an Large Language Model (LLM)-based education tools.
g. Incorporate rubrics for assessments through Application Programming Interface (API).
h. Read and write spreadsheet data with vibe coding and compile grade computions from learning management systems (LMS).
i. Guide learners in using GPT-based tools for ideation, iteration, and reflection in design thinking.
j. Identify when a course-specific chatbot offers more value than a generic AI chatbot.
k. Develop and deploy a chatbot as a standalone link or frame.
Entry Requirements
a. Basic coding knowledge
b. Basic video editing skills
Course Details
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