Course Description:
This course introduces students to modern applied AI practices for creating real academic and professional deliverables. Students learn foundational AI concepts and failure modes, then use AI to design and execute multi-step workflows that can support writing, research, analysis, and product creation (e.g., prototypes, websites, and automation scripts). Emphasis is placed on reliability: students evaluate outputs using test plans and rubrics, verify claims with credible sources, document decisions in process logs, and apply responsible-use practices related to privacy, bias, and disclosure. Students complete a portfolio of AI-assisted artifacts and demonstrate mastery through an oral workflow walkthrough.
Assessment-First Design:
Any major
(freshman–senior)
None
(or "basic college writing recommended")
Upon successful completion of this course, students will be able to:
Explain common generative AI capabilities and limitations, including frequent failure modes.
Design AI-assisted workflows with defined goals, constraints, and success criteria for academic and professional tasks.
Evaluate AI outputs using rubrics, test cases, and counterexample checks, and revise based on findings.
Verify factual claims using credible sources and document source traces and confidence levels.
Apply responsible-use practices related to privacy, bias, disclosure, and academic integrity.
Produce a portfolio of AI-assisted artifacts with complete process documentation and reflective analysis.
We don't just teach GenAI—we teach reliability. Students learn to design, test, verify, and defend AI-assisted workflows with professional-grade rigor.
Students document prompts, iterations, and version history—complete transparency of their workflow
Claim ledger mapping every statement to a source or flagging it as unverified
Test cases, counterexamples, and reliability scoring—students prove outputs work
3–5 minute presentations where students explain their process and reasoning
Curated professional work with full documentation—evidence of competency development
Clear assessment criteria that work at scale—from 30 students to 3,000
Built for professional credibility and institutional confidence
Students produce work they can show employers. Institutions get defensible outcomes.
Project-based learning with hands-on deliverables—students build, test, and deploy real work.
Understanding capabilities, limitations, hallucinations, bias, and when AI breaks.
Designing repeatable workflows with goals, constraints, success criteria, and revision loops.
Students choose a track and create a professional artifact using AI workflows.
Choose Your Track:
Building evaluation plans, running test cases, verifying claims, and documenting confidence levels.
Responsible use practices, institutional policies, risk management, and disclosure norms.
Students curate their best work with complete documentation and present their process, findings, and evidence.
Each studio is hands-on and deliverable-focused. Students don't just learn about AI—they build, test, verify, and present real work with professional documentation.
See what students actually produce—professional artifacts with full process documentation.
Students build a test plan, run variants, score outputs against defined criteria—then write a reliability report documenting what worked and what failed.
Student Artifacts Produced:
Students create a claim ledger mapping every factual statement to primary sources, label confidence levels (High/Medium/Low), and identify claims that cannot be verified.
Student Artifacts Produced:
Students write an acceptable-use policy for a real organization scenario (university department, startup, nonprofit), including stakeholder analysis, risk assessment, and governance recommendations.
Student Artifacts Produced:
Every lab includes rubrics, templates, and example artifacts so students know exactly what's expected.
Reduce friction—get from partnership to first class in under 2 hours.
Complete Materials Package
Syllabus, slides, labs, rubrics, templates—everything ready to use
LMS-Ready Files
Import to Canvas, Blackboard, or Moodle with one click
Teacher Guide
Week-by-week walkthrough with instructional strategies and pacing guidance
Policy Pack
Sample acceptable-use policies your institution can adopt
Instructor Onboarding
60–90 minute training session + Q&A (virtual or on-site)
Ongoing Support
Email/chat access during semester + quarterly Q&A sessions
Optional: PD Workshop
Half-day faculty development workshop for department-wide adoption
Optional: Customization
Adapt materials to your institution's branding or discipline needs
Total implementation time: Under 2 hours from
onboarding to first class.
We handle curriculum development—you focus on teaching.
Request access to watermarked sample materials—see exactly what you're getting.
Materials are watermarked for preview only. Full access provided upon partnership agreement.
We'll send materials within 1 business day. No spam—just the preview pack.
Common questions about implementation and scalability
Let's discuss how this course fits your institution's needs and explore partnership opportunities.