| Language of instruction : English |
| Exam contract: not possible |
| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master Biostatistics | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical |  |
| 1st year Master Biostatistics - icp | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical | |
| 1st year Quantitative Epidemiology | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical | |
| 1st year Master Quantitative Epidemiology - icp | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software. | | | - DC
| ... correctly using state-of-the-art software. | - EC
| The student is able to efficiently acquire, store and process data. | | | - DC
| ... selecting and using the best data management options |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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In this course, students will be made familiar with relational as well as document- and graph-databases. They will learn how to model data in each, and how to load/process/extract data.
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Distance learning ✔
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Lecture ✔
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Small group session ✔
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Period 1 Credits 5,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| 1st year Master Data Science | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical | |
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| | | Learning outcomes |
- EC
| The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software. | | | - DC
| ... correctly using state-of-the-art software. | - EC
| The student is able to efficiently acquire, store and process data. | | | - DC
| ... selecting and using the best data management options |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
In this course, students will be made familiar with relational as well as document- and graph-databases. They will learn how to model data in each, and how to load/process/extract data.
|
|
|
|
|
|
|
|
|
Distance learning ✔
|
|
|
|
Lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
Period 1 Credits 5,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
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| 1st year Master Bioinformatics | Optional | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical | |
| Exchange Programme Statistics | Optional | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software. | | | - DC
| ... correctly using state-of-the-art software. | - EC
| The student is able to efficiently acquire, store and process data. | | | - DC
| ... selecting and using the best data management options |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
In this course, students will be made familiar with relational as well as document- and graph-databases. They will learn how to model data in each, and how to load/process/extract data.
|
|
|
|
|
|
|
|
|
Distance learning ✔
|
|
|
|
Lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
Period 1 Credits 5,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
|
|
1 examination regulations art.1.3, section 4. |
| 2 examination regulations art.4.7, section 2. |
3 examination regulations art.2.2, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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