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:
Este curso faz parte do Programa de cursos integrados Analytics for Decision Making
oferecido por
Programa de cursos integrados Analytics for Decision MakingUniversidade de MinnesotaUniversidade de MinnesotaInformações sobre o curso
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Curso 3 de 4 no
Nível iniciante
Familiarity with Excel spreadsheets
Aprox. 14 horas para completar
Inglês
Legendas: Inglês
Habilidades que você terá
AnalyticsOperations ManagementLinear Programming (LP)Mathematical Optimization
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 3 de 4 no
Nível iniciante
Familiarity with Excel spreadsheets
Aprox. 14 horas para completar
Inglês
Legendas: Inglês
oferecido por
Universidade de MinnesotaUniversidade de Minnesota
The University of Minnesota is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
Programa - O que você aprenderá com este curso
4 horas para concluir
Module 1: LPs for Financial Decisions
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.
4 horas para concluir
14 vídeos (Total 111 mín.), 1 leitura, 2 testes
3 horas para concluir
Module 2: LP for Supply Chain Decisions
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.
3 horas para concluir
10 vídeos (Total 53 mín.)
3 horas para concluir
Module 3: LP for Staffing Decisions
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.
3 horas para concluir
11 vídeos (Total 67 mín.), 1 leitura, 2 testes
4 horas para concluir
Module 4: LP for Production Decisions
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.
4 horas para concluir
11 vídeos (Total 56 mín.), 3 leituras, 2 testes
Avaliações
Principais avaliações do ADVANCED MODELS FOR DECISION MAKING
por NR18 de Set de 2021
The concepts are explained well. The lectures are very detail oriented. I just wish there were more examples to follow.
por JH2 de Jun de 2021
All of the courses in this series are very practical based and give a lot of practice in using the tools.
por CL18 de Mai de 2021
Really enjoyed the lesson. Learned application of optimization analytics in various setting.
Sobre Programa de cursos integrados Analytics for Decision Making
The field of analytics is typically built on four pillars: Descriptive Analytics, Predictive Analytics, Causal Analytics, and Prescriptive Analytics. Descriptive analytics (e.g., visualization, BI) deal with the exploration of data for patterns, predictive analytics (e.g., data mining, time-series forecasting) identifies what can happen next, causal modeling establishes causation, and prescriptive analytics help with formulating decisions. This specialization focuses on the Prescriptive Analytics (the final pillar). This specialization will review basic predictive modeling techniques that can be used to estimate values of relevant parameters, and then use optimization and simulation techniques to formulate decisions based on these parameter values and situational constraints. The specialization will teach how to model and solve decision-making problems using predictive models, linear optimization, and simulation methods.
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