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
| 担当者 | Rehaf Foula |
|---|---|
| 最終更新 | 2026/10/18 |
| メンバー | 1 |
IT & related technologies
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1. AI Leadership Context1レッスン ·
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1.1 Welcome新規
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2. Opportunity Discovery5レッスン ·
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2.1 AI Opportunity Signals新規
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2.2 Workflow Friction Mapping新規
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2.3 Value Pool Prioritization新規
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2.5 Strategic Use Case Patterns新規
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2.6 Executive Problem Briefs新規
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3. Solution Architecture7レッスン ·
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3.1 AI Solution Building Blocks新規
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3.2 Model Capability Mapping新規
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3.3 Data And Context Design新規
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3.4 Tool And Agent Boundaries新規
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3.5 Human Control Points新規
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3.6 Architecture Tradeoff Review新規
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3.7 Design A Solution Blueprint新規
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4. Models And Tools9レッスン ·
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4.1 Foundation Model Landscape新規
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4.2 Model Selection Criteria新規
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4.3 Prompt System Design新規
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4.4 Structured Output Controls新規
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4.5 Tool Calling Patterns新規
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4.7 Agent Framework Choices新規
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4.8 Automation Platform Options新規
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4.9 Cost Latency Decisions新規
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4.10 Select A Production Stack新規
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5. Data And Knowledge8レッスン ·
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5.1 Enterprise Data Readiness新規
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5.2 Knowledge Source Inventory新規
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5.3 Data Quality Diagnostics新規
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5.4 Document Processing Flows新規
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5.5 Retrieval Augmentation Design新規
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5.6 Embedding And Index Choices新規
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5.7 Knowledge Access Permissions新規
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5.8 Data Lineage For AI新規
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6. Prototype To Product10レッスン ·
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6.1 Prototype Success Criteria新規
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6.2 Rapid Experiment Design新規
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6.3 Prompt And Workflow Tests新規
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6.4 Evaluation Dataset Construction新規
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6.5 Quality Metric Selection新規
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6.6 Human Review Protocols新規
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6.8 Prototype Demonstration Design新規
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6.9 Pilot Backlog Planning新規
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6.10 Product Requirements For AI新規
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6.11 Build A Validated Prototype新規
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7. AI Governance8レッスン ·
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7.1 Governance Operating Principles新規
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7.2 Risk Classification Methods新規
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7.3 Privacy And Security Controls新規
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7.4 Responsible Use Standards新規
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7.5 Model And Vendor Due Diligence新規
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7.6 Approval Workflow Design新規
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7.7 Incident Response For AI新規
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7.8 Create A Governance Playbook新規
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8. Production Operations9レッスン ·
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8.1 Production Readiness Gates新規
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8.2 Deployment Architecture Choices新規
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8.3 Observability For AI Systems新規
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8.4 Monitoring Quality Drift新規
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8.5 Cost And Capacity Management新規
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8.7 Release And Rollback Controls新規
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8.8 Model Lifecycle Management新規
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8.9 Service Ownership Models新規
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8.10 Production Launch Review新規
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9. AI Risk Decisions6レッスン ·
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9.1 Bias And Fairness Signals新規
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9.2 Reliability And Hallucination新規
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9.3 Explainability Requirements新規
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9.4 Adversarial Threat Scenarios新規
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9.5 Risk Acceptance Decisions新規
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9.6 Escalation And Remediation新規
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10. Adoption And Change5レッスン ·
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10.1 AI Adoption Readiness新規
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10.2 Stakeholder Impact Mapping新規
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10.3 Role Redesign Conversations新規
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10.5 Enablement And Training Plans新規
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10.6 Trust And Communication Metrics新規
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11. Portfolio And Scale10レッスン ·
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11.1 AI Portfolio Strategy新規
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11.2 Investment Sequencing Models新規
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11.3 Platform Versus Product新規
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11.4 Operating Model Options新規
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11.5 Capability And Talent Planning新規
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11.6 Partner Ecosystem Design新規
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11.7 Benefits Realization Systems新規
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11.8 Scaling Pattern Selection新規
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11.9 Executive Decision Forums新規
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11.10 Build A Scale Roadmap新規
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12. Executive Capstone1レッスン ·
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12.1 Key Takeaways新規
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