Get qualified automatically after earning CSAI®
Chartered Supply Chain Artificial Intelligence Analyst (CSAI)®
The next wave of technology - artificial
intelligence (AI) - is already making sense of the
deluge of operational data streaming in from a plethora of devices and cloud applications. This technology is also applying advanced mathematics to create products, processes, and systems that can adapt and learn.
Machine learning capabilities apply algorithms to massive opera- tional data feeds to discover insights to track and predict supply chain disruptions, providing new levels of visibility into day-to-day operations. These capabilities can also recommend alternative ac- tions for unplanned events and transportation disruptions. Weath- er data integrated with operational data can predict potential problems and alert transportation and logistics service personnel with recommended actions.
Topics evaluated in CSAI®
- Machine learning in Supply Chain
- Machine learning (ML) techniques
- ML algorithms
- How to apply ML in demand forecasting, sales and operation planning (S&OP), and inventory management
- ML in production planning and predictive maintenance
- Forecasting
- Advanced analytics techniques using engine downtime predictive modeling example
American Association of Procurement and Supply Chain Management (AAPSCM)®
Machine learning in Supply Chain
1) Powering the planning revolution to Identify stock fluctuations.
2) Forecast trends and demands for products.
3) Detect excesses and shortages of assets in a store.
4) Optimize production planning.
How to apply ML in demand forecasting, sales and operation planning (S&OP), and inventory management
1) Use cases of AI/ML in Supply Chain.
2) Ensemble Methods in Predicting customer’s behavior.
3) Genetic algorithms for improving delivery times and reducing costs.
Forecasting
1) Demand Forecast and Fulfillment with AI.
2) Blockchain-backed immutability and trust.
ML algorithms
1) AI solutions for Pain points in supply chain management.
2) Potential role of AI in the supply chain.
3)Necessary algorithms & Tools and framework.
Machine learning (ML) techniques
1) Predict customer demand and optimize production planning.
2)Optimize routing decisions for vehicles.
3)Provide end-to-end visibility from suppliers to customers.
4)Automate order fulfillment.
ML in production planning and predictive maintenance
1) Representation Leaning in Supply Chain.
2)Deep Reinforcement Learning in building effective supply chain optimization models.
Advanced analytics techniques using engine downtime predictive modeling example
1) Predictive Monitoring and Techniques.
2)Exploring predictive analytics and test what-if scenarios
in analytics apps, with real-time calculations.
CSAI® Virtual/Online Instructor-led 4-day Training
Time
4-Day Training
Fees
$1,200
Address
Dallas, Texas Charter and
Conference Center (AAPSCM)®
Instructor
Jason matyus
Dr. Matyus is the Advisory Board Director for Course Development, Training, and Examination. Dr. Jason Matyus’s career spans many disciplines. Dr. Matyus started as a public school teacher. After leaving teaching he worked for 20 years as a business professional working for two Fortune 500 Companies.
Gleb Mikulich
Gleb Mikulich is a seasoned professional with over a decade of expertise in supply chain, procurement, logistics, and digital transformation. He has collaborated with globally recognized organizations, including Accenture, Procter & Gamble (P&G), Pfizer, CNH Industrial, and Mediterranean Shipping Company, delivering impactful solutions across diverse industries.
