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:
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Analytics for Decision Making
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von
Spezialisierung Analytics for Decision MakingUniversity of MinnesotaÜber diesen Kurs
3.805 kürzliche Aufrufe
Flexible Fristen
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Zertifikat zur Vorlage
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100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 3 von 4 in
Stufe „Anfänger“
Familiarity with Excel spreadsheets
Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Kompetenzen, die Sie erwerben
- Analytics
- Operations Management
- Linear Programming (LP)
- Mathematical Optimization
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 3 von 4 in
Stufe „Anfänger“
Familiarity with Excel spreadsheets
Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch
von
University of 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.
Lehrplan - Was Sie in diesem Kurs lernen werden
4 Stunden zum Abschließen
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 Stunden zum Abschließen
14 Videos (Gesamt 111 min), 1 Lektüre, 2 Quiz
3 Stunden zum Abschließen
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 Stunden zum Abschließen
10 Videos (Gesamt 53 min)
3 Stunden zum Abschließen
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 Stunden zum Abschließen
11 Videos (Gesamt 67 min), 1 Lektüre, 2 Quiz
4 Stunden zum Abschließen
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 Stunden zum Abschließen
11 Videos (Gesamt 56 min), 3 Lektüren, 2 Quiz
Bewertungen
- 5 stars81,81 %
- 4 stars18,18 %
Top-Bewertungen von ADVANCED MODELS FOR DECISION MAKING
von JH2. Juni 2021
All of the courses in this series are very practical based and give a lot of practice in using the tools.
von NR18. Sep. 2021
The concepts are explained well. The lectures are very detail oriented. I just wish there were more examples to follow.
von CL18. Mai 2021
Really enjoyed the lesson. Learned application of optimization analytics in various setting.
Über den Spezialisierung 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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