Duration:

5 online sessions × 2–2.5 hours each (delivered across 5 consecutive days)

Who Should Attend:

• AI product managers and solution architects
• ML and data engineering leads
• Business and technology consultants
• Sponsors and stakeholders of AI adoption programs

Training Outcomes:

• Master the full lifecycle of AI product development
• Use structured frameworks to reduce build-risk and improve ROI
• Align business goals with technical AI capabilities
• Embed responsible AI principles across every stage of delivery
• Build reusable, modular, and scalable solution blueprints

Course Topics:

1. Strategic Framing for AI Projects
   • Identifying business problems suited for AI
   • Stakeholder alignment and value mapping
   • Metrics for success and impact
2. AI Product Lifecycle & Frameworks
   • 5D model: Discover → Design → Develop → Deploy → Drive
   • User-centricity meets model pipelines
   • Workflow visualisation and toolkits
3. Responsible AI by Design
   • Bias, fairness, and transparency
   • Risk classification and ethical checkpoints
   • Internal policies and external compliance
4. Technical Architecture & Delivery
   • MLops, cloud services, and API integration
   • Deployment patterns and retraining cycles
   • DevOps for scalable AI
5. Operationalisation and Scaling
   • Change enablement and capability building
   • Business communication and value realisation
   • Portfolio thinking for AI delivery

#AISolutions #AIDesign #AIProjects #DigitalTransformation #InnovationTechnology #AIEngineering #TechLeadership #London #USA #Turkey