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
| Ответственный | Rehaf Foula |
|---|---|
| Последнее обновление | 18.10.2026 |
| Участники | 1 |
IT & related technologies
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1. AI Leadership Context1Уроки -
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1.1 WelcomeНовый
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2. Opportunity Discovery5Уроки -
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2.1 AI Opportunity SignalsНовый
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2.2 Workflow Friction MappingНовый
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2.3 Value Pool PrioritizationНовый
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2.5 Strategic Use Case PatternsНовый
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2.6 Executive Problem BriefsНовый
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3. Solution Architecture7Уроки -
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3.1 AI Solution Building BlocksНовый
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3.2 Model Capability MappingНовый
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3.3 Data And Context DesignНовый
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3.4 Tool And Agent BoundariesНовый
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3.5 Human Control PointsНовый
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3.6 Architecture Tradeoff ReviewНовый
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3.7 Design A Solution BlueprintНовый
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4. Models And Tools9Уроки -
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4.1 Foundation Model LandscapeНовый
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4.2 Model Selection CriteriaНовый
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4.3 Prompt System DesignНовый
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4.4 Structured Output ControlsНовый
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4.5 Tool Calling PatternsНовый
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4.7 Agent Framework ChoicesНовый
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4.8 Automation Platform OptionsНовый
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4.9 Cost Latency DecisionsНовый
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4.10 Select A Production StackНовый
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5. Data And Knowledge8Уроки -
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5.1 Enterprise Data ReadinessНовый
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5.2 Knowledge Source InventoryНовый
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5.3 Data Quality DiagnosticsНовый
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5.4 Document Processing FlowsНовый
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5.5 Retrieval Augmentation DesignНовый
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5.6 Embedding And Index ChoicesНовый
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5.7 Knowledge Access PermissionsНовый
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5.8 Data Lineage For AIНовый
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6. Prototype To Product10Уроки -
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6.1 Prototype Success CriteriaНовый
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6.2 Rapid Experiment DesignНовый
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6.3 Prompt And Workflow TestsНовый
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6.4 Evaluation Dataset ConstructionНовый
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6.5 Quality Metric SelectionНовый
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6.6 Human Review ProtocolsНовый
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6.8 Prototype Demonstration DesignНовый
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6.9 Pilot Backlog PlanningНовый
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6.10 Product Requirements For AIНовый
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6.11 Build A Validated PrototypeНовый
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7. AI Governance8Уроки -
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7.1 Governance Operating PrinciplesНовый
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7.2 Risk Classification MethodsНовый
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7.3 Privacy And Security ControlsНовый
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7.4 Responsible Use StandardsНовый
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7.5 Model And Vendor Due DiligenceНовый
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7.6 Approval Workflow DesignНовый
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7.7 Incident Response For AIНовый
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7.8 Create A Governance PlaybookНовый
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8. Production Operations9Уроки -
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8.1 Production Readiness GatesНовый
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8.2 Deployment Architecture ChoicesНовый
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8.3 Observability For AI SystemsНовый
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8.4 Monitoring Quality DriftНовый
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8.5 Cost And Capacity ManagementНовый
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8.7 Release And Rollback ControlsНовый
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8.8 Model Lifecycle ManagementНовый
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8.9 Service Ownership ModelsНовый
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8.10 Production Launch ReviewНовый
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9. AI Risk Decisions6Уроки -
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9.1 Bias And Fairness SignalsНовый
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9.2 Reliability And HallucinationНовый
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9.3 Explainability RequirementsНовый
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9.4 Adversarial Threat ScenariosНовый
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9.5 Risk Acceptance DecisionsНовый
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9.6 Escalation And RemediationНовый
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10. Adoption And Change5Уроки -
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10.1 AI Adoption ReadinessНовый
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10.2 Stakeholder Impact MappingНовый
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10.3 Role Redesign ConversationsНовый
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10.5 Enablement And Training PlansНовый
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10.6 Trust And Communication MetricsНовый
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11. Portfolio And Scale10Уроки -
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11.1 AI Portfolio StrategyНовый
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11.2 Investment Sequencing ModelsНовый
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11.3 Platform Versus ProductНовый
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11.4 Operating Model OptionsНовый
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11.5 Capability And Talent PlanningНовый
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11.6 Partner Ecosystem DesignНовый
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11.7 Benefits Realization SystemsНовый
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11.8 Scaling Pattern SelectionНовый
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11.9 Executive Decision ForumsНовый
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11.10 Build A Scale RoadmapНовый
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12. Executive Capstone1Уроки -
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12.1 Key TakeawaysНовый
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