| Uitgebreide vaknaam |
Data Analysis and Programming for OM |
| Leerdoelen |
1. Extract, transform, analyze, and visualize real data: B.3
2. Develop a basic mathematical model
3. Link data manipulation tools with mathematical models through programming in Python |
| Omschrijving |
Quantitative models are powerful and important tools in Operations Management decision making. Examples are inventory models, scheduling heuristics, facility layout design, vehicle routing, and maintenance policies. Organizations collect more and more data through Enterprise Resource Planning systems, Manufacturing Execution Systems, and Internet of Things, giving more opportunities for employing these mathematical models. The descriptions of mathematical models usually presume clear-cut and clean input data. In practice, however, it is difficult to get such data as it is often messy and unclear how to extract data from systems. Consequently, to be useful in mathematical models, manufacturing and demand data need to be extracted, transformed, filtered, linked, analyzed, and visualized. The course Data Analysis and Programming for OM addresses this by combining data science, programming, and mathematical modeling. This involves developing basic mathematical models for OM problems, processing real data, and linking them through programming in Python. The basic skills prepare for and are used in subsequent courses in the TOM program. |
| Uren per week |
5 |
| Onderwijsvorm |
-computer practicum, -hoorcollege , -werkcollege
(combined lecture-tutorial)
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| Toetsvorm |
-individueel mondeling tentamen, -individuele opdracht
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| Vaksoort |
master
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| Coördinator |
dr. W.M.C. van Wezel
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| Docent(en) |
N.G. Merkelijn, MSc.
,Dr. N.B. Szirbik
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| Verplichte literatuur |
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Auteur |
ISBN |
Prijs |
| Literature will be electronically available and announced at the start of the course |
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| Entreevoorwaarden |
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| Opmerkingen |
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