Data Science for Business (4853) |
| Language of instruction : English |
| Credits: 6,0 | | | | Period: semester 2 (6sp)  | | | | | 2nd Chance Exam1: Yes | | | | | Final grade2: Numerical |
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Sequentiality
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Advising sequentiality bound on the level of programme components
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Following programme components are advised to also be included in your study programme up till now.
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Process and Data Modelling (4851)
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6.0 stptn |
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This concerns a transition curriculum. No contact sessions are provided. The student is only required to participate in the evaluation.
In an era where data has become the new oil, understanding the role it plays in business decision-making is essential for every professional. This course is designed to equip students with the fundamental knowledge of data science and its application to business decision-making.
The course will explore various methods and concepts of machine learning. By understanding these concepts, students will learn how machines can be trained to predict outcomes and identify patterns in a dataset, respectively. Subsequently, students wll also learn how to evaluate the quality of these analytical models. Here, learners will be introduced to metrics and techniques for assessing the performance and predictive power of these models.
By the end of this course, students will have a solid understanding of the role data science plays in business. They will be able to harness data to uncover insights, drive business strategies, and create impactful data narratives.
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Lecture ✔
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Response lecture ✔
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Small group session ✔
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Semester 2 (6,00sp) Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory textbooks (bookshop) |
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Data Science for Business: What you need to know about data mining and data-analytic thinking.,Provost, Foster, and Tom Fawcett,2013.,O'Reilly Media, Inc.
ISBN: 978-1449361327 |
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| Recommended course material |
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Dit opleidingsonderdeel maakt gebruik van DataCamp For The Classroom, aangeboden door DataCamp (www.datacamp.com) |
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| Remarks |
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This concerns a transition curriculum. No contact sessions are provided. The student is only required to participate in the evaluation. |
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Learning outcomes | | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
| Offered in | Tolerance3 |
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Exchange Programme Business Economics
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J
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Master of Management Data Science
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J
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.15.1, section 3. |
3 Education, Examination and Legal Position Regulations art.16.9, section 2.
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