- Level Professional
- Course by University of California, Irvine
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Offered by
About
Over the past two decades, the supply chain has become more complex. While advancing technology has allowed companies to capture this complexity within stores of ever accumulating data, companies have not kept up with how to analyze and derive insights from that data. This specialization uses hands-on activities to show how data science techniques can turn raw data into decision-makers for a more agile supply chain. Foundational techniques such as demand forecasting, inventory management with demand variability, and using the newsvendor model are covered, in addition to more advanced techniques such as how to optimize for capacity and resources as well as mitigate risks with the Monte Carlo simulation. By the end of this specialization, you will be able to: Describe how demand planning, supply planning, and constrained forecast are associated with one another. Use Excel to analyze historical data to quantify future needs. Analyze historical data to determine inventory levels in steady and uncertain demand situations using Excel. Manage inventory in an uncertain environment. Quantify the inventory needs for single-period items using the newsvendor model. Identify the components of capacity optimization, resource optimization, and Monte Carlo simulation. Set up and solve optimization problems in Excel. Build a demand and inventory snapshot and run a Monte Carlo simulation to solve for a more agile supply chain.Auto Summary
Transform your supply chain with data science through this professional-level course. Dive into demand forecasting, inventory management, capacity optimization, and risk mitigation using Excel and Monte Carlo simulations. Ideal for IT and Computer Science professionals, this hands-on course, led by Coursera, offers both starter and professional subscription options for flexible learning.

Instructor
Paul Jan