Industry AI Co-creation Lab
Focus: University-industry co-creation, real industry projects, and an approved public case library
Overview
Brings NTPU AI Learn outcomes into real industry problems. Multidisciplinary experts, industry sponsors, domain experts, and project teams jointly frame problems, build proof of value, assess readiness, run controlled pilots, and use measurable evidence to decide whether to adopt, scale, iterate, or stop. Not every AI idea should be implemented: a well-supported No-Go is also a valuable outcome.
5 courses · Representative courses: IL 101 · IL 201 · IL 202
Project lifecycle
A real industry project moves through the following stages from discovery to the case library. Not every learner completes every course, since the actual path depends on role and project needs.
- 1.Discovery Discovery & prioritization
Find and prioritize candidate AI use cases through AD 101-103.
- 2.IL 101 Project & Value Design
Turn a selected use case into a Project Charter, passing Gate 1, the Value Gate.
- 3.IL 201 Proof of Value
Build a prototype and use evidence to decide whether it is worth further investment, passing Gate 2, the Evidence Gate.
- 4.IL 202 Data & Governance Readiness
Assess data, security, privacy, and integration readiness, passing Gate 3, the Readiness Gate.
- 5.IL 301 Pilot & Adoption
Run a controlled real-world pilot, passing Gate 4, the Adoption Gate.
- 6.IL 302 Transformation, Scale & Value Realization
Turn a successful pilot into an enterprise transformation roadmap, passing Gate 5, the Scale Review.
- 7.Case Library Case Library
After project completion, sponsor, IP/privacy, and academic review must all approve before an approved case is published.
Project roles
Every real industry project brings together several roles, each responsible for a different part of the work.
- Industry Sponsor：Validates the business problem and target KPIs, enables access to people/evidence, joins key decision gates, and supports adoption decisions.
- Process / Business Owner：Owns the workflow affected by the project.
- Domain Expert：Provides operational/domain knowledge.
- NTPU Cross-domain Advisor：Responsible for framing, evidence quality, domain/business guidance, and academic standards.
- AI / Data Advisor：Responsible for technical feasibility, architecture, data, and evaluation reliability.
- Project Team：Typically 3-5 learners.
- Transformation Advisor (optional)：May be an experienced executive, external consultant, alumnus, or technology partner, bringing industry practice.
Industry project intake
An organization with an established partnership can submit a project intake through its organization workspace, describing the problem, current state, target outcome, and available evidence, for joint review by NTPU staff and the organization contact.
- Identify the executive sponsor and business/process owner
- Describe the problem statement, current workflow, and baseline
- Describe the target outcome and measurable success metrics
- Describe available data/evidence and security/privacy constraints
- Joint review by NTPU staff and the organization contact
An organization member can find "Start a new project" inside their organization workspace. Organizations without a partnership yet: see "Partner with us" below.
Industry AI Case Library
Reviewed, publicly approved Industry Co-creation cases: successful adoptions and well-supported No-Go decisions alike.
View casePrivacy, IP & data
Industry projects may involve processes, data summaries, and learner submissions an organization has shared, and these are always treated as sensitive: stored only in managed locations, shared only with authorized people, and handled per the project data retention policy.
- Projects declare a data classification (D0 public/synthetic through D4 prohibited for the course environment), which determines which data modes are permitted.
- IP status (background IP, project-created IP, code/model/data ownership, publication rights) must be confirmed before IL 201/IL 301 begins.
- Sponsor contact details, internal documents, confidential evaluation data, and raw learner submissions never appear in public cases or public APIs.
Certificates
Completing each IL course's required artifact and passing review earns the matching skill certificate; attendance alone does not.
- IL 101: AI Skill Certificate, Industry AI Project & Value Design
- IL 201: Industry AI Proof-of-Value Certificate
- IL 202: AI Skill Certificate, Enterprise AI Readiness
- IL 301: Enterprise AI Pilot Certificate
- IL 302: AI Skill Certificate, Enterprise AI Transformation & Value Realization
Completing IL 101 through IL 302 and passing a final portfolio review earns the "NTPU Enterprise AI Transformation Series Certificate."
The series certificate marks completion of the full pathway. It is not a Professional Certification, which would require a separate certification scheme.
Partner with us
The Industry AI Co-creation Lab welcomes partnerships of many shapes, jointly framing real problems and using evidence to decide whether to adopt.
- One-off project partners
- Anchor partners
- Joint labs
- Sponsored cohorts
- Multi-company consortiums
- Public-sector partners
- Nonprofit / social-impact partners
Organizations interested in partnering are welcome to reach out through NTPU AI4X, describing your problem domain and the kind of partnership you have in mind.
Propose a partnershipPartnership request
Tell us about your organization's partnership interest. The NTPU Industry AI Co-creation Lab team will review your request and follow up.
FAQ
What counts as a "real industry project"?
It needs a clear business problem, an executive sponsor and a business/process owner, and a measurable target outcome, and it cannot be simple software procurement: synthetic data, de-identified data, or controlled enterprise data are all acceptable; unrestricted production access is not required.
Is our company data safe?
Project data is always treated as sensitive and accessible only to authorized people. Sponsor contact details and confidential content never appear on public pages or public APIs. Publishing a public case requires sponsor, IP/privacy, and academic review to all approve first.
What if we decide not to adopt (No-Go)?
A well-supported No-Go is a successful learning outcome the Industry AI Co-creation Lab recognizes, not a failure. The case library also preserves valuable No-Go and lessons-learned cases.
Do I need to code to take part?
Not necessarily. IL 101 and IL 302 are aimed mainly at business and management roles and need no coding. IL 201/IL 202/IL 301 need a team with matching AI/data capability, typically as a cross-role team effort.
Can learners who have not taken an IL course join a project team?
IL 201 and IL 301 require an approved Project Charter and the matching prerequisite course. We recommend completing IL 101 (or having equivalent experience) before joining a project team, so the team shares a common project vocabulary and evaluation approach.
Does finishing a project always publish a public case?
No. Course completion never auto-publishes a project. A public case needs sponsor approval, IP/privacy review, and academic quality review, all to pass, and the project may instead stay private or go teaching-anonymized only.
Who typically takes part in a project?
The core team is the executive sponsor, business/process owner, NTPU cross-domain advisor, AI/data advisor, and a project team of 3-5 learners; higher-risk projects add legal/governance, security/privacy, or change-management advisors.
Do IL certificates count as a professional certification?
No. IL certificates are skill/series certificates marking completion of the matching course and artifact review. They are not currently a formal Professional Certification.