| Language of instruction: English |
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Mandatory sequentiality bound on the level of programme components
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Following programme components must have been included in your study programme in a previous education period
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Programming in Python (3306)
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5.0 stptn |
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There is no data for this choice. Change the language, year or choose another item in the dropdown list if it is available.
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| Degree programme | | Study hours | Credits | P2 SBU | P2 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master Bioinformatics | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical |  |
| 1st year Master Bioinformatics - icp | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical |  |
| 1st year Master Data Science | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
| The student is capable of acquiring new knowledge. | - EC
| The student is able to efficiently acquire, store and process data. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The students can write simple imperative programs in Python. In particular, they can utilize primitive types, strings, lists, dictionnaries, sets, iteration, conditions, procedures and functions, and they can debug programs.
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This course introduces advanced Python topics, such as regular expressions, files and exceptions, object oriented programming and recursion, as well as basic algortihms on graphs, pandas and numpy.
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Lecture ✔
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Practical ✔
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Project ✔
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Self-study assignment ✔
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Exercises ✔
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Homework ✔
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Semester 2 (5,00sp)
| Evaluation method | |
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| Written evaluation during teaching period | 60 % |
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| Transfer of partial marks within the academic year | ✔ |
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| Written exam | 40 % |
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| Transfer of partial marks within the academic year | ✔ |
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| Evaluation conditions (participation and/or pass) | ✔ |
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| Conditions | A minimum score of 40% on each of the three components of the evaluation (assignments, project and final exam) is required to pass the course. |
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| Consequences | The student will receive a score of maximum 9/20. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory textbooks (bookshop) |
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[Intro to Python for computer science and data science],[Paul Deitel, Harvey Deitel],[First edition],[Pearson],[9780135404676],[] |
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 | Exchange Programme Computer Science | Optional | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical |  |
| Exchange Programme Statistics | Optional | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical |  |
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The students can write simple imperative programs in Python. In particular, they can utilize primitive types, strings, lists, dictionnaries, sets, iteration, conditions, procedures and functions, and they can debug programs.
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This course introduces advanced Python topics, such as regular expressions, files and exceptions, object oriented programming and recursion, as well as basic algortihms on graphs, pandas and numpy.
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Lecture ✔
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Practical ✔
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Project ✔
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Self-study assignment ✔
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Exercises ✔
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Homework ✔
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Semester 2 (5,00sp)
| Evaluation method | |
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| Written evaluation during teaching period | 60 % |
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| Transfer of partial marks within the academic year | ✔ |
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| Written exam | 40 % |
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| Transfer of partial marks within the academic year | ✔ |
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| Evaluation conditions (participation and/or pass) | ✔ |
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| Conditions | A minimum score of 40% on each of the three components of the evaluation (assignments, project and final exam) is required to pass the course. |
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| Consequences | The student will receive a score of maximum 9/20. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory textbooks (bookshop) |
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[Intro to Python for computer science and data science],[Paul Deitel, Harvey Deitel],[First edition],[Pearson],[9780135404676],[] |
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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