Live AI courses and workshops for project managers
Compare PM-specific courses with affirmative instructor-led delivery evidence. Mixed routes stay labeled; confirm current dates, time zones and attendance requirements.
Match the class to your next task
Stanford University IT describes project artifacts, dashboards and a capstone across a longer workshop. Learning Tree focuses on project risk in a one-day instructor-led route. Cprime describes broader AI applications to project management. These are different curricula, not a ranking.
For a live class, check the time zone, session attendance requirements, tool access, class exercises and feedback. A course certificate is separate from a professional designation; read the credit and credential conditions on each profile.
12 instruction hours; campus clock 9–4 includes longer elapsed time · 1,200 (currency not stated) — live online posted dollars; Campus: 1,550 (currency not stated); Group quote: 5+same team quote
Learning Tree International
1 day. · GBP 690 (page displays GBP 690); tax basis is not stated.
Cprime
Standard: 14 hours over 2 days; Scheduled: Oct 14–16, Nov 9–11, Dec 7–9; 12–4:30 Eastern across 3 dates · 1,350 USD — per person; Groups of 3+: 1,250 USD
These are provider-described conditions from recorded source checks. Open each profile for its source date and limitations; confirm current enrollment terms before paying.
Eight modules move from safe daily AI use and capability vocabulary to use-case/value selection, prompting as specification, solution/data readiness/prototyping, running AI projects, economics/security/risk/governance and portfolio adoption/capstone.
Evaluate AI models and apply AI to planning, task management, risk tracking, reporting, scope, scheduling, meeting summaries and stakeholder communications; review bias, confidentiality and output fitness.
DIALOG prompt method and GenAI use through project opportunity/business case/charter, preparation/specification/WBS/schedule/critical path/risk/budget, execution/progress/decisions/change and closure/lessons learned.
Covers AI fundamentals and limits, project process automation, planning/tracking/reporting, AI-agent workflow design, project insights and performance, governance, ethics, risk, change and adoption roadmaps.
and a reviewed AI project capstone/application plan. Named outputs include a use-case scorecard, prompt pack, charter/WBS/milestones, RAID register/change brief, meeting/action records, checked status workbook/management pack, PMO workflow/checklist and role-specific project pack.
Live / instructor-ledEnglish, Arabic or bilingual by team choice
Day one covers lifecycle use cases, scope/schedule/WBS support, resource/cost/scenario analysis and risk identification/mitigation. Day two covers progress analysis and early-warning indicators, executive dashboards/status narratives, stakeholder/meeting workflows, governance, confidentiality and an implementation plan.
The 17-module published syllabus ranges from AI foundations and PMO maturity through planning/scheduling, resource/capacity, predictive risks, cost/budget, quality, governance/reporting, portfolio scenarios, stakeholder engagement, workflow automation, data governance, tool integration, PMO change and responsible AI.
University of Wisconsin–Milwaukee School of Continuing Education
Use AI for estimates, forecasts, uncertainty, risk and change-impact decisions; turn analysis into executive recommendations with human accountability.
University of Pretoria Enterprises / Project Management South Africa
Topics include AI and the changing project-manager role, Generative AI/GPTs, prompt engineering, ChatGPT as a project-work assistant, truth-checking/hallucination awareness, useful PM prompts and blockchain/smart-contract applications in project management.