Certified AI in Supply Chain & Logistics Specialist (C-AISCLS) Certification Program by Tonex
Harness AI to forecast demand, optimize inventory, and orchestrate logistics with precision. This program builds practical mastery in predictive analytics, digital twin design, and end-to-end demand optimization across retail, manufacturing, and distribution networks. You will model supply variability, detect early signals from sales and external data, and choose the right optimization strategy for sourcing, warehousing, and last-mile delivery. Digital twins help you simulate network changes, evaluate constraints, and quantify ROI before you commit capital or time.
Security is first-class throughout. You will learn how to protect data pipelines across suppliers, safeguard model integrity from tampering and data poisoning, and enforce access controls in MLOps. We cover encryption, secure feature stores, and auditability so your AI remains trustworthy and compliant. By graduation, you will connect business KPIs to resilient AI workflows that scale reliably, reduce risk, and drive measurable margin gains.
Learning Objectives:
- Build demand-sensing models and evaluate accuracy.
- Design supply and logistics optimizers with constraints.
- Create digital twins for networks, sites, and flows.
- Operationalize AI with robust data and MLOps.
- Quantify impact using business and service KPIs.
- Implement cybersecurity controls for AI supply chains.
Audience:
- Supply Chain Managers and Planners
- Logistics and Operations Leaders
- Data Scientists and Analysts
- IT/OT Architects and Platform Engineers
- Product and Program Managers
- Cybersecurity Professionals
Program Modules:
Module 1: AI Foundations for Supply & Logistics
- AI use-cases across plan, source, make, deliver
- Data landscape: ERP, WMS, TMS, IoT, external feeds
- Feature engineering for time series and events
- Model selection: forecasting, classification, RL
- KPI mapping: service, cost, cash, risk
- Change management and adoption
Module 2: Demand Sensing & Predictive Analytics
- Short-term vs long-term forecasting approaches
- Causal, hierarchical, and intermittent demand
- Nowcasting from POS, web, weather, promos
- Forecast accuracy, bias, and uplift tracking
- Consensus planning and override governance
- Scenario planning for uncertainty
Module 3: Digital Twins for Supply Networks
- Twin scope: network, facility, lane, and SKU
- Data fidelity, synchronization, and latency
- Constraint modeling and what-if analysis
- Capacity, lead-time, and service trade-offs
- Stress tests and resilience heatmaps
- ROI and decision traceability
Module 4: Optimization & Execution Intelligence
- Inventory policies and multi-echelon planning
- Replenishment, allocation, and ATP logic
- Network design and transportation routing
- Slotting, picking, and yard optimization
- Event-driven orchestration with agents
- Exceptions, alerts, and control-tower views
Module 5: Data Engineering, MLOps & Quality
- Data contracts and lineage across systems
- Batch vs streaming pipelines and CDC
- Feature stores and reproducible training
- CI/CD for models and drift monitoring
- Cost, latency, and reliability SLAs
- Compliance, retention, and audits
Module 6: Security, Ethics & Compliance
- Threats: data poisoning and model theft
- Encryption, key management, and access control
- Supplier data sharing and federated learning
- Policy, governance, and responsible AI
- Regulatory considerations and standards
- Incident response for AI workflows
Exam Domains:
- Strategic AI for Supply Chain Advantage
- Data Integrity, Lineage, and Interoperability
- Predictive Risk, Continuity, and Resilience
- Optimization Performance and Business KPIs
- Secure MLOps and Access Governance
- Compliance, Ethics, and Audit Readiness
Course Delivery:
The course is delivered through lectures, interactive discussions, and project-based learning led by experts in Certified AI in Supply Chain & Logistics Specialist (C-AISCLS). Participants receive curated online resources, readings, case studies, and guided exercises that reinforce practical decision-making.
Assessment and Certification:
Participants are assessed through quizzes, assignments, and a capstone project. Upon successful completion, participants receive a certificate in Certified AI in Supply Chain & Logistics Specialist (C-AISCLS).
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified AI in Supply Chain & Logistics Specialist (C-AISCLS) Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to modernize your supply chain with secure, high-impact AI? Enroll now. Bring your data, questions, and goals—leave with a roadmap and the skills to execute.