Overview
Master AI in Operations: Supply Chain Optimization, Predictive Maintenance, Demand Forecasting, AI-Driven Quality Contr
Syllabus
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- Introduction to AI in Operations Management
-- Overview of AI applications in operations
-- Historical context and evolution
- Fundamentals of Supply Chain Optimization with AI
-- AI techniques in supply chain management
-- Real-time inventory management
- Advanced Strategies in Supply Chain Management
-- Machine learning for demand forecasting
-- AI-driven supply chain resilience
- Predictive Maintenance Techniques
-- Introduction to predictive analytics
-- Case studies on predictive maintenance
- Demand Forecasting
-- AI models for accurate forecasting
-- Tools and technologies
- Quality Control Enhancement with AI
-- Automated inspection systems
-- Machine vision applications
- Workforce Management Optimization
-- AI in scheduling and resource allocation
-- Enhancing productivity with AI tools
- Strategic Decision-Making and AI
-- AI in business strategy formulation
-- Decision-making tools and frameworks
- AI Tools for Dynamic Pricing Strategies
-- Algorithms for pricing optimization
-- Case examples of dynamic pricing
- Transformative AI Technologies in Operations
-- Overview of AI innovations
-- Industry-specific applications
- Real-World Applications and Case Studies
-- In-depth case studies
-- Practical examples and outcomes
- Capstone Projects and Practical Implementations
-- Project design and development
-- Portfolio building with AI projects
- Collaborative Workshops and Presentations
-- Team-based learning sessions
-- Presentation of findings and solutions
- Conclusion and Future Directions in AI and Operations
-- Trends and future opportunities
-- Career pathways and development in AI-driven operations
- Course Recap and Final Assessment
-- Review of key concepts
-- Final project presentation and assessment
Taught by
Peter Alkema and Irlon Terblanche
Tags
On-Demand
