Ai & Machine Learning For Predictive Demand Forecasting & Optimization: Future-proofing Supply Chain Efficiency

Introduction

AI & Machine Learning for Predictive Demand Forecasting & Optimization training equips professionals to leverage advanced algorithms and data analytics to accurately forecast demand and optimize supply chain operations. This course focuses on analyzing historical data, implementing machine learning models, and understanding the impact of AI-driven insights on supply chain efficiency. Participants will learn to develop predictive models, utilize optimization techniques, and understand the intricacies of using AI to minimize inventory costs and improve customer satisfaction. By mastering AI and machine learning in demand forecasting and optimization, professionals can enhance their ability to create agile and responsive supply chains, reduce waste, and drive significant cost savings.

The increasing complexity of global supply chains and the growing need for data-driven decision-making necessitate a comprehensive understanding of AI and machine learning applications. This course delves into the nuances of time series analysis, regression modeling, and optimization algorithms, empowering participants to develop and implement tailored solutions. By integrating data science skills with supply chain domain knowledge, this program enables organizations to lead initiatives that maximize operational efficiency and drive long-term competitive advantage.

Target Audience:

• Supply chain analysts
• Demand planners
• Inventory managers
• Data scientists
• Logistics managers
• Operations managers
• Business analysts
• IT professionals
• Project managers
• Consultants
• Retail professionals
• Manufacturing professionals
• Individuals interested in AI and machine learning in supply chain

Course Objectives:

• Understand the fundamentals of AI and machine learning and their application in demand forecasting and optimization.
• Implement techniques for preparing and preprocessing data for machine learning models.
• Understand the role of time series analysis in demand forecasting.
• Implement techniques for developing and evaluating regression and machine learning models for demand prediction.
• Understand the principles of optimization algorithms and their application in supply chain management.
• Implement techniques for utilizing AI to optimize inventory management and logistics operations.
• Understand the role of AI in improving supply chain resilience and responsiveness.
• Implement techniques for conducting scenario analysis and what-if simulations using AI.
• Understand the legal and ethical considerations related to AI in supply chain.
• Implement techniques for integrating AI models with existing supply chain systems.
• Understand the economic and operational benefits of AI adoption in demand forecasting and optimization.
• Develop strategies for managing AI-driven supply chain projects.
• Develop strategies for measuring and analyzing the effectiveness of AI implementations.

DURATION

10 Days

COURSE CONTENT

Module 1: AI & Machine Learning Fundamentals:

• Introduction to AI and machine learning concepts
• Types of machine learning algorithms (supervised, unsupervised, reinforcement)
• Applications of AI in supply chain management
• Data-driven decision making
• Overview of predictive analytics

Module 2: Data Preparation and Preprocessing:

• Data collection and cleaning techniques
• Feature engineering and selection
• Handling missing data and outliers
• Data transformation and normalization
• Data splitting and validation

Module 3: Time Series Analysis:

• Time series decomposition and analysis
• Autoregressive Integrated Moving Average (ARIMA) models
• Seasonal forecasting techniques
• Time series cross-validation
• Evaluating time series forecasting performance

Module 4: Regression and Machine Learning Models:

• Linear and polynomial regression
• Decision trees and random forests
• Support vector machines (SVMs)
• Neural networks and deep learning
• Model selection and hyperparameter tuning

Module 5: Optimization Algorithms:

• Linear programming and optimization
• Constraint optimization techniques
• Heuristic and metaheuristic algorithms
• Simulation-based optimization
• Applications in inventory and logistics optimization

Module 6: Inventory and Logistics Optimization:

• AI-driven inventory management strategies
• Optimizing warehouse operations and logistics routes
• Demand-driven replenishment and distribution
• Predictive maintenance and asset management
• Real-time optimization techniques

Module 7: Supply Chain Resilience and Responsiveness:

• AI-based risk management and disruption detection
• Adaptive supply chain planning and execution
• Dynamic rerouting and logistics optimization
• Real-time monitoring and control systems
• Building agile and resilient supply chains

Module 8: Scenario Analysis and What-If Simulations:

• Developing simulation models for supply chain scenarios
• Conducting sensitivity analysis and risk assessment
• Evaluating the impact of external factors and disruptions
• Using AI to generate and evaluate alternative scenarios
• Supporting strategic decision-making

Module 9: Legal and Ethical Considerations:

• Data privacy and security regulations
• Ethical implications of AI in decision-making
• Bias and fairness in machine learning models
• Compliance with industry-specific regulations
• Responsible AI development and deployment

Module 10: AI Model Integration:

• Integrating AI models with ERP and supply chain systems
• API development and data exchange
• Cloud-based AI platforms and services
• Building data pipelines and workflows
• Deployment and maintenance of AI models

Module 11: Economic and Operational Benefits:

• Cost reduction and efficiency gains
• Improved inventory management and customer service
• Enhanced supply chain visibility and control
• Faster response times and reduced lead times
• Competitive advantage and market leadership

Module 12: AI-Driven Project Management:

• Project planning and execution for AI initiatives
• Stakeholder engagement and communication
• Risk management and mitigation
• Budgeting and resource allocation
• Performance monitoring and evaluation

Module 13: Performance Measurement and Analysis:

• Key performance indicators (KPIs) for AI projects
• Evaluating model accuracy and performance
• Measuring ROI and business impact
• Continuous improvement and model refinement
• Reporting and documentation

Module 14: Advanced Machine Learning Techniques:

• Deep reinforcement learning.
• Graph neural networks.
• Ensemble modeling methods.
• Automated machine learning.
• Advanced time series methods.

Module 15: Future trends in AI for supply chain:

• Digital twin technology.
• Edge AI deployment.
• Quantum machine learning.
• Autonomous supply chains.
• The Metaverse and supply chain implications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 5 working days before commencement of the training.