Live AI courses and workshops for project managers · page 2
Compare PM-specific courses with affirmative instructor-led delivery evidence. Mixed routes stay labeled; confirm current dates, time zones and attendance requirements.
AI for scoping, task structuring, risk/issue/dependency identification, stakeholder communication and documentation, status reports, dashboards, meeting outputs, governance, AI risk and a project-improvement plan.
Uses ChatGPT and Gemini to produce a project-document toolkit from a realistic scenario: initiation/charter, scope and schedule, cost and resource plans, risk register, stakeholder work, execution and earned-value monitoring, issue/performance reporting, closeout and post-project evaluation. Includes privacy and responsible-use guidance.
The provider outline includes AI fundamentals and project cases, identifying AI opportunities, predictive scheduling and forecasting, risk and issue tracking, resource allocation, dashboards, governance, privacy, change management and a digital PM roadmap.
prompts for charters/scope/WBS, activities/dependencies and three-point estimates
risk triggers and early warnings
status/meeting automation
capacity planning
privacy and human-review checkpoints. Day-five labs build a charter/WBS/estimate, risk register/early-warning report, tested prompt library, team AI policy and a PM playbook.
Use a realistic AI/hybrid project case to plan, identify, analyze, respond to and monitor project risks; build a risk breakdown structure and register, apply qualitative scoring and Expected Monetary Value/decision trees, and define response, fallback and dashboard indicators.
benefits and executive reporting. Methods include ISO31000 risk registers, DORA indicators, conceptual Monte Carlo/anomaly detection, human-reviewed AI estimates and NIST AI RMF review gates.
and responsible use. Stated outputs include AI-supported WBS/schedule, charter/status and stakeholder communications, risk/contingency plans, PMO workflow automation, a prompt library and adoption plan.
Covers AI-supported initiation, charters, scope, WBS/backlogs, estimation, scheduling and scenarios, RAID/risk management, capacity, stakeholder reporting, privacy and governance; ends with an implementation lab and capstone on configuring PM tools and measuring a pilot.
Use an AI PM workspace for status, meetings and risks; select low-risk agent tasks, write delegation briefs, redesign a workflow with human ownership/QA and develop an agent-system blueprint.
The five-day outline moves from AI/data and PM tool analysis to an AI-driven schedule scenario and resource-allocation model, predictive risk assessment/monitoring, responsible integration and team change, then a practical AI-PM tool exercise and personal implementation action plan.