📚 Syllabus & Course Curriculum
AI & Machine Learning in Healthcare
Module-by-module breakdown of AI for Supply Chain Management: Optimizing Logistics with Artificial Intelligence, from foundations to a certified capstone project.
Outline
Subsection 1.1.1: Understanding the Supply Chain Key components: Procurement, manufacturing, warehousing, transportation, and distribution. • Challenges in traditional supply chains: Delays, inefficiencies, and lack of real-time visibility.
Outline
Subsection 2.1.1: Types of Data in Supply Chain Structured data: Inventory levels, sales orders, delivery times. • Unstructured data: Supplier communication, customer feedback. • External data: Weather patterns, market trends, and geopolitical events.
Outline
Subsection 3.1.1: Traditional vs AI-Driven Demand Forecasting Limitations of traditional forecasting methods. • How AI improves accuracy using historical and external data.
Outline
Subsection 4.1.1: AI for Warehouse Monitoring Automating inventory counts with computer vision. • Real-time alerts for anomalies in warehouse operations.
Outline
Subsection 5.1.1: Ensuring GDPR and CCPA Compliance Safeguarding customer and partner data.
Earn government-registered certification in AI for Supply Chain Management: Optimizing Logistics with Artificial Intelligence
e-Certificate and e-Marksheet issued on successful completion.
