Business analysts need to be able to prescribe optimal solution to problems. But analytics courses are often focused on training students in data analysis and visualization, not so much in helping them figure out how to take the available data and pair that with the right mathematical model to formulate a solution. This course is designed to connect data and models to real world decision-making scenarios in manufacturing, supply chain, finance, human resource management, etc. In particular, we understand how linear optimization - a prescriptive analytics method - can be used to formulate decision problems and provide data-based optimal solutions. Throughout this course we will work on applied problems in different industries, such as:
Advanced Models for Decision Making
This course is part of Analytics for Decision Making Specialization
Instructor: Soumya Sen
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There are 4 modules in this course
In this module we will look at examples illustrating the application of linear optimization in finance. In particular, we will learn to formulate problems in investment portfolio optimization and multi-period cash flow management.
What's included
14 videos1 reading2 assignments
This module explores the use of linear optimization in supply chain decisions, particularly in the context of inventory transportation or logistics problems as well as in production and inventory management.
What's included
10 videos2 assignments
This module explores how human resource managers can use optimization as a prescriptive analytics tool to plan staff schedules, room allocation, and workforce size management.
What's included
11 videos1 reading2 assignments
Linear optimization plays an important role in the decision making process in the manufacturing sector. This module explores how optimization can be used to prescribe product mix and blending decisions.
What's included
11 videos3 readings2 assignments1 discussion prompt
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University of Colorado Boulder
New York University
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