About Course
Level 2: AI PRACTITIONER – AI Roadmap for Educators
This course shifts the focus from simple interactions to the science of the prompt. Faculty will move beyond basic “ask-and-receive” methods to learn structured frameworks (like RICO, CARE, or the 5S Model) and advanced logical techniques such as Chain-of-Thought and Few-Shot Prompting. By the end, faculty will be able to build complex, multi-step instructions that can generate entire course modules, specialized rubrics, and personalized student simulations.
Benefits of Attending
- Precision: Stop getting “vague” answers and start getting exact educational materials.
- Scalability: Create “Power Prompts” that can be used semester after semester.
- Logic Mastery: Learn to guide AI through complex reasoning, making it a better co-teacher.
Expected Outcomes
- A personal “Prompt Engineering Playbook” featuring advanced structures.
- Proficiency in multimodal prompting (using images, PDFs, and data as inputs).
- Ability to “Debug” poor AI outputs by identifying structural flaws in the prompt.
Course Content
Module 1: The Anatomy of a Practitioner’s Prompt
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The Anatomy of a Practitioner’s Prompt
00:00 -
Module 1 Quiz
Module 2: Prompting Frameworks—RICO & The 5S Model
Module 3: Few-Shot Prompting & In-Context Learning
Module 4: Chain-of-Thought (CoT) & Logic Scaffolding
Module 5: Advanced Output Formatting (Markdown & Tables)
Module 6: Iterative Refinement & Feedback Loops
Module 7: Multimodal Prompting: Beyond Text
Module 8: Capstone—Building a Shared Prompt Library
Course Conclusion and Summary
Download: Prompt Engineering Quick Reference
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