AI Solution Leadership Lab
Designed for managers and leaders who need to turn business opportunities into responsible, scalable AI-powered solutions. By the end, participants will be able to select high-value use cases, design and build AI workflows and agents with modern tools, evaluate performance and risk, and lead successful deployment and adoption.
5.000,00 LE
5000.0
EGP
5.000,00 LE
| Responsabile | Rehaf Foula |
|---|---|
| Ultimo aggiornamento | 18/10/2026 |
| Iscritti | 1 |
IT & related technologies
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1. AI Leadership Context1Lezioni ·
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1.1 WelcomeNuovo
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2. Opportunity Discovery5Lezioni ·
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2.1 AI Opportunity SignalsNuovo
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2.2 Workflow Friction MappingNuovo
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2.3 Value Pool PrioritizationNuovo
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2.5 Strategic Use Case PatternsNuovo
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2.6 Executive Problem BriefsNuovo
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3. Solution Architecture7Lezioni ·
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3.1 AI Solution Building BlocksNuovo
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3.2 Model Capability MappingNuovo
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3.3 Data And Context DesignNuovo
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3.4 Tool And Agent BoundariesNuovo
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3.5 Human Control PointsNuovo
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3.6 Architecture Tradeoff ReviewNuovo
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3.7 Design A Solution BlueprintNuovo
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4. Models And Tools9Lezioni ·
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4.1 Foundation Model LandscapeNuovo
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4.2 Model Selection CriteriaNuovo
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4.3 Prompt System DesignNuovo
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4.4 Structured Output ControlsNuovo
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4.5 Tool Calling PatternsNuovo
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4.7 Agent Framework ChoicesNuovo
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4.8 Automation Platform OptionsNuovo
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4.9 Cost Latency DecisionsNuovo
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4.10 Select A Production StackNuovo
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5. Data And Knowledge8Lezioni ·
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5.1 Enterprise Data ReadinessNuovo
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5.2 Knowledge Source InventoryNuovo
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5.3 Data Quality DiagnosticsNuovo
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5.4 Document Processing FlowsNuovo
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5.5 Retrieval Augmentation DesignNuovo
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5.6 Embedding And Index ChoicesNuovo
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5.7 Knowledge Access PermissionsNuovo
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5.8 Data Lineage For AINuovo
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6. Prototype To Product10Lezioni ·
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6.1 Prototype Success CriteriaNuovo
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6.2 Rapid Experiment DesignNuovo
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6.3 Prompt And Workflow TestsNuovo
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6.4 Evaluation Dataset ConstructionNuovo
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6.5 Quality Metric SelectionNuovo
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6.6 Human Review ProtocolsNuovo
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6.8 Prototype Demonstration DesignNuovo
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6.9 Pilot Backlog PlanningNuovo
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6.10 Product Requirements For AINuovo
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6.11 Build A Validated PrototypeNuovo
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7. AI Governance8Lezioni ·
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7.1 Governance Operating PrinciplesNuovo
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7.2 Risk Classification MethodsNuovo
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7.3 Privacy And Security ControlsNuovo
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7.4 Responsible Use StandardsNuovo
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7.5 Model And Vendor Due DiligenceNuovo
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7.6 Approval Workflow DesignNuovo
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7.7 Incident Response For AINuovo
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7.8 Create A Governance PlaybookNuovo
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8. Production Operations9Lezioni ·
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8.1 Production Readiness GatesNuovo
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8.2 Deployment Architecture ChoicesNuovo
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8.3 Observability For AI SystemsNuovo
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8.4 Monitoring Quality DriftNuovo
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8.5 Cost And Capacity ManagementNuovo
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8.7 Release And Rollback ControlsNuovo
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8.8 Model Lifecycle ManagementNuovo
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8.9 Service Ownership ModelsNuovo
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8.10 Production Launch ReviewNuovo
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9. AI Risk Decisions6Lezioni ·
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9.1 Bias And Fairness SignalsNuovo
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9.2 Reliability And HallucinationNuovo
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9.3 Explainability RequirementsNuovo
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9.4 Adversarial Threat ScenariosNuovo
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9.5 Risk Acceptance DecisionsNuovo
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9.6 Escalation And RemediationNuovo
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10. Adoption And Change5Lezioni ·
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10.1 AI Adoption ReadinessNuovo
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10.2 Stakeholder Impact MappingNuovo
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10.3 Role Redesign ConversationsNuovo
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10.5 Enablement And Training PlansNuovo
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10.6 Trust And Communication MetricsNuovo
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11. Portfolio And Scale10Lezioni ·
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11.1 AI Portfolio StrategyNuovo
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11.2 Investment Sequencing ModelsNuovo
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11.3 Platform Versus ProductNuovo
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11.4 Operating Model OptionsNuovo
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11.5 Capability And Talent PlanningNuovo
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11.6 Partner Ecosystem DesignNuovo
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11.7 Benefits Realization SystemsNuovo
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11.8 Scaling Pattern SelectionNuovo
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11.9 Executive Decision ForumsNuovo
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11.10 Build A Scale RoadmapNuovo
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12. Executive Capstone1Lezioni ·
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12.1 Key TakeawaysNuovo
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