EXECUTIVE SUMMARY
Data Analytics & AI in Supply Chain Management is a transformative course designed to empower professionals with cutting-edge skills to harness data-driven decision-making and artificial intelligence in optimizing supply chain operations. This course explores predictive analytics, machine learning applications, and AI-powered tools to enhance forecasting accuracy, inventory optimization, logistics efficiency, and risk management. Through real-world case studies and hands-on exercises, participants will learn to leverage big data and intelligent automation to drive cost savings and competitive advantage. Suitable for both tech-savvy professionals and beginners, this course offers flexible learning formats to master the future of smart supply chains.
INTRODUCTION
In an era where data is the new oil, supply chains generate massive amounts of information that—when properly analyzed—can unlock unprecedented efficiency gains. This course bridges the gap between traditional supply chain management and modern data science, teaching participants how to apply AI and analytics to solve complex challenges like demand volatility, supplier disruptions, and route optimization. You'll gain practical experience with tools like Python for supply chain analytics, AI-driven demand sensing platforms, and digital twin simulations. By course completion, you'll be equipped to implement data-centric strategies that transform supply chains from cost centers to value drivers.
COURSE OBJECTIVES
- Master fundamental concepts of data analytics in supply chain contexts
- Apply machine learning techniques for demand forecasting and inventory optimization
- Utilize AI to enhance logistics routing and warehouse operations
- Implement predictive maintenance models for supply chain equipment
- Develop data visualization dashboards for supply chain KPIs
- Understand how blockchain combines with AI for supply chain transparency
- Build AI models to mitigate risks and detect supply chain fraud
- Leverage natural language processing (NLP) for supplier contract analysis
- Create digital twins for supply chain scenario planning
TARGET AUDIENCE
- Supply chain managers seeking digital transformation skills
- Logistics professionals aiming to adopt AI solutions
- Data scientists transitioning to supply chain applications
- Operations managers responsible for inventory optimization
- Procurement specialists implementing predictive analytics
- IT professionals developing supply chain AI systems
- Consultants advising on smart supply chain strategies
- Graduates pursuing careers in logistics technology
COURSE OUTLINE
Day 1: Foundations of Supply Chain Analytics
- Evolution from traditional to data-driven supply chains
- Key data types and sources in supply chain ecosystems
- Building a data infrastructure for supply chain visibility
Day 2: Predictive Analytics for Supply Chains
- Time-series forecasting techniques for demand planning
- Machine learning models for inventory optimization
- Hands-on: Building demand forecasts with Python
Day 3: AI in Logistics & Transportation
- Route optimization algorithms using machine learning
- AI-powered dynamic pricing for freight
- Case study: How Amazon uses AI in last-mile delivery
Day 4: Intelligent Warehouse Management
- Computer vision for inventory tracking
- Robotics process automation in warehouses
- AI-driven warehouse layout optimization
Day 5: Risk Management with AI
- Predictive models for supply chain disruptions
- AI-based supplier risk assessment
- Simulation: Managing a supply chain crisis with AI tools
COURSE DURATION
- 5-Day Intensive: Bootcamp style with hands-on labs
- 2-Week Executive Version: For senior professionals
- 4-Week Comprehensive: With capstone project
- Available in virtual, hybrid, and in-person formats
INSTRUCTOR
Led by PhD-level data scientists and supply chain practitioners with proven experience implementing AI solutions at Fortune 500 companies.
FREQUENTLY ASKED QUESTIONS
Q: Do I need programming experience?
A: Basic understanding helps but we offer beginner tracks.
Q: What software will we use?
A: Python, Tableau, Power BI, and leading AI platforms.
Q: How is this different from generic data science courses?
A: 100% focused on supply chain applications with industry-specific datasets.
Q: Can we implement these techniques in traditional companies?
A: Yes, we cover phased adoption strategies for all maturity levels.
Q: Is certification provided?
A: Yes, with optional NASBA CPE credits for US professionals.
