Designed for
- Analysts
- Knowledge teams
- Researchers
- Organizations
Intermediate · Knowledge systems
AI Data & Knowledge Systems: build capability you can prove.
Build a source-grounded knowledge workflow that another person can inspect, test, and operate responsibly.
Knowledge systemsData & Knowledge
A governed knowledge workflow with quality checks, retrieval structure, citations, and an evidence-based review process.
Program overview
Learn the method. Build the system. Retain the proof.
A systems program for preparing information, structuring knowledge, designing retrieval, grounding answers, and maintaining quality over time.
Practical outcomeA governed knowledge workflow with quality checks, retrieval structure, citations, and an evidence-based review process.
Build a source-grounded knowledge assistant or retrieval workflow using approved information.
Who this is for
A clear fit before you invest your time.
The application and readiness diagnostic help Admissions confirm fit, preparation, delivery mode, and any support needed.
Before you begin
- Comfort working with documents or structured information
- Access to an approved, non-sensitive practice dataset
- Basic familiarity with AI assistants
Capabilities developed
- Data preparation
- Knowledge design
- Retrieval
- Citations
- Quality review
Program roadmap
A complete learning sequence—not disconnected lessons.
Each stage prepares the next, with practical work, review, and evidence connected to the intended capability.
Information readiness
Audit sources, ownership, permissions, quality, duplication, sensitivity, and intended use.
Knowledge architecture
Structure documents, metadata, taxonomies, chunks, relationships, and update responsibilities.
Retrieval and grounding
Design search, retrieval, context assembly, citations, missing-answer behavior, and source traceability.
Quality and evaluation
Test relevance, completeness, faithfulness, freshness, access boundaries, and failure recovery.
Operation and governance
Document ingestion, review, retention, monitoring, feedback, and continuous improvement.
Learning experience
Live guidance, entitled practice, a real build, and human review.
Live systems teaching
Eligible Program-linked Labs practice where confirmed
Source-quality reviews
Human-reviewed implementation capstone
Program-linked Labs
Labs scope is confirmed before enrollment
Eligible Labs and usage conditions are confirmed in the Program offer before enrollment.
Program-included access is granted only when verified enrollment, Program, prerequisites, policy, access dates, usage conditions, and an active Program entitlement permit it. Included eligible Labs carry no separate Labs subscription charge. Chatoner Class access alone does not include Labs.
Project & evidence
The credential direction is backed by work another person can inspect.
AI may support practice and organize evidence. Authorized human educators retain final authority over assessment, completion, credentials, discipline, and safeguarding.
What can follow
Use the result as a foundation—not a finish line.
Live cohort delivery
Dates are published only after the cohort is confirmed.
A confirmed cohort connects instructor-led Class sessions, eligible AI Labs, project work, human feedback, and proof-backed completion. No public date or availability is currently published.
01Live teaching in Chatoner Class02Entitled practice in AI Labs03Project and human feedback04Evidence and credential review
Ready to apply?
Start the application for Data & Knowledge.
Complete your profile, program choice, readiness, goals, project, schedule, funding, consent, and final review—then track the human-reviewed admissions decision.