| Language of instruction : English |
| Exam contract: not possible |
|
Sequentiality
|
| |
|
No sequentiality
|
| Degree programme | | Study hours | Credits | P4 SBU | P4 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master of Biomedical Sciences - Environmental Health Sciences | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical |  |
| 1st year Master of Biomedical Sciences - Molecular Mechanisms in Health and Disease | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| 2. A graduate of the Master of Biomedical Sciences can independently and critically perform a literature search. | - EC
| 4. A graduate of the Master of Biomedical Sciences has knowledge of state-of-the-art techniques within biomedical research and is able to apply these techniques, taking into account the applicable quality standards. | - EC
| 5. A graduate of the Master of Biomedical Sciences can independently process and statistically analyze research results, and formulate conclusions. | - EC
| 7. A graduate of the Master of Biomedical Sciences takes a critical attitude towards one's own research and that of others. | - EC
| 12. A graduate of the Master of Biomedical Sciences has an attitude for lifelong learning and for constantly adjusting one's own professional thinking and acting. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
In this course the students will get acquainted with systematic reviews, data repositories and handling and processing of large datasets.
The learning goals are as follows:
The students can perform a systematic review and make a study flow chart.
The students are aware of data repositories and are able to collect data.
The students can indepently perform basic skills in managing and manupulating data in a reproducable way.
The students can independently generate plots such as volcano plots, ideograms, etc. from big datasets.
|
|
|
|
|
|
|
|
|
Practical ✔
|
|
|
|
Project ✔
|
|
|
|
|
|
|
|
Demonstration ✔
|
|
|
|
Report ✔
|
|
|
|
Period 4 Credits 3,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 100 % |
|
|
|
|
|
|
|
|
| Prerequisites |
| |
Basic knowledge of statistics:
- Confidence intervals
- Hypothesis testing
- Lineair regression
- ANOVA
|
|
|
|
|
|
| first year Master of Biomedical Sciences - Clinical Biomedical Sciences | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| 2. A graduate of the Master of Biomedical Sciences can independently and critically perform a literature search | - EC
| 4. A graduate of the Master of Biomedical Sciences has knowledge of state-of-the-art techniques within biomedical research and is able to apply these techniques, taking into account the applicable quality standards. | - EC
| 5. A graduate of the Master of Biomedical Sciences can independently process and statistically analyze research results, and formulate conclusions. | - EC
| 7. A graduate of the Master of Biomedical Sciences takes a critical attitude towards one's own research and that of others. | - EC
| 12. A graduate of the Master of Biomedical Sciences has an attitude for lifelong learning and for constantly adjusting one's own professional thinking and acting. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
In this course the students will get acquainted with systematic reviews, data repositories and handling and processing of large datasets.
The learning goals are as follows:
The students can perform a systematic review and make a study flow chart.
The students are aware of data repositories and are able to collect data.
The students can indepently perform basic skills in managing and manupulating data in a reproducable way.
The students can independently generate plots such as volcano plots, ideograms, etc. from big datasets.
|
|
|
|
|
|
|
|
|
Practical ✔
|
|
|
|
Project ✔
|
|
|
|
|
|
|
|
Demonstration ✔
|
|
|
|
Report ✔
|
|
|
|
Period 4 Credits 4,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 100 % |
|
|
|
|
|
|
|
|
| Prerequisites |
| |
Basic knowledge of statistics:
- Confidence intervals
- Hypothesis testing
- Lineair regression
- ANOVA
|
|
|
|
|
|
| 1st year Master of Biomedical Sciences - Bioelectronics and Nanotechnology | Optional | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| 2. A graduate of the Master of Biomedical Sciences can independently and critically perform a literature search. | - EC
| 4. A graduate of the Master of Biomedical Sciences has knowledge of state-of-the-art techniques within biomedical research and is able to apply these techniques, taking into account the applicable quality standards. | - EC
| 5. A graduate of the Master of Biomedical Sciences can independently process and statistically analyze research results, and formulate conclusions. | - EC
| 7. A graduate of the Master of Biomedical Sciences takes a critical attitude towards one's own research and that of others. | - EC
| 12. A graduate of the Master of Biomedical Sciences has an attitude for lifelong learning and for constantly adjusting one's own professional thinking and acting. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
In this course the students will get acquainted with systematic reviews, data repositories and handling and processing of large datasets.
The learning goals are as follows:
The students can perform a systematic review and make a study flow chart.
The students are aware of data repositories and are able to collect data.
The students can indepently perform basic skills in managing and manupulating data in a reproducable way.
The students can independently generate plots such as volcano plots, ideograms, etc. from big datasets.
|
|
|
|
|
|
|
|
|
Practical ✔
|
|
|
|
Project ✔
|
|
|
|
|
|
|
|
Demonstration ✔
|
|
|
|
Report ✔
|
|
|
|
Period 4 Credits 3,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 100 % |
|
|
|
|
|
|
|
|
| Prerequisites |
| |
Basic knowledge of statistics:
- Confidence intervals
- Hypothesis testing
- Lineair regression
- ANOVA
|
|
|
|
|
|
| Master of Teaching in Health Sciences keuzetraject BMW/GEN met vakdidactiek biologie | Optional | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
| Master of Teaching in Health Sciences keuzetraject BMW/GEN met vakdidactiek chemie | Optional | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| The newly graduated student can perform literature research in an independent and critical manner, formulate and operationalise a research question or hypothesis, collect research data, and process, interpret and report orally and in writing on the obtained research results. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
In this course the students will get acquainted with systematic reviews, data repositories and handling and processing of large datasets.
The learning goals are as follows:
The students can perform a systematic review and make a study flow chart.
The students are aware of data repositories and are able to collect data.
The students can indepently perform basic skills in managing and manupulating data in a reproducable way.
The students can independently generate plots such as volcano plots, ideograms, etc. from big datasets.
|
|
|
|
|
|
|
|
|
Practical ✔
|
|
|
|
Project ✔
|
|
|
|
|
|
|
|
Demonstration ✔
|
|
|
|
Report ✔
|
|
|
|
Period 4 Credits 3,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 100 % |
|
|
|
|
|
|
|
|
| Prerequisites |
| |
Basic knowledge of statistics:
- Confidence intervals
- Hypothesis testing
- Lineair regression
- ANOVA
|
|
|
|
|
|
1 examination regulations art.1.3, section 4. |
| 2 examination regulations art.4.7, section 2. |
3 examination regulations art.2.2, section 3.
|
| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
|