Core Module Information
Module title: Prescriptive Analytics

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: SOE11168
Module leader: Max Chipulu
School The Business School
Subject area group: Management
Prerequisites

There are no pre-requisites for this module to be added

Description of module content:

Decision-Making for OrganizationsOrganizations face many complex decisions every day. They need to find the best solutions to these problems in order to run their operations and plan for the future efficiently and effectively. This module will teach you how to use prescriptive analytics techniques to formulate and solve decision problems optimally.Part 1: OptimizationOptimization techniques use models to find the best solutions to problems with multiple variables and constraints. These techniques can be used to solve a wide range of problems in business, such as resource planning, investment planning, machine scheduling, logistics, and supply chain management.Part 2: SimulationSimulation is a technique that uses computer models to represent and analyse real-world systems. Simulation can be used to study a wide range of systems, including operational systems (such as hospitals, airports, and supermarkets) and strategic systems (such as the healthcare system and the supply chain).This module will give you the skills and knowledge you need to use prescriptive analytics to make better decisions in your organization.

Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Appraise and formulate an optimisation problem.

LO2: Critically evaluate the appropriateness of optimisation techniques and software to model and solve diverse business problems.

LO3: Demonstrate a critical understanding of the different types of simulation techniques and have insight into the domains in which we can usefully apply each.

LO4: Model and solve business decision problems using the appropriate simulation techniques and software.

LO5: Explain the results of your prescriptive model to non-technical business users in a way that is easy to understand.

Full Details of Teaching and Assessment

Indicative References and Reading List - URL:
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