NBIB20000U Python Programming for Data Science
BSc Programme in Biochemistry
BSc Programme in Biology
BSc Programme in Molecular Biomedicine
MSc Programme in Bioinformatics
This course is an introduction to programming in Python, with focus on data processing and analysis. It includes basic programming concepts such as data types, conditionals, loops, functions, object oriented programming, pattern matching (regular expressions), and computational complexity. In addition, it also provides technical skills relevant to the data science pipeline such as the ability to log on to an external server, and to navigate a Unix shell.
After completing the course, the student will master key programming concepts such as data-types, variables, conditionals, loops, and functions, and have an understanding of the central concepts in object oriented programming, pattern matching and computational complexity. Finally, the student will have acquired an understanding of a Unix/Linux environment, including basic navigation, pipes, networking, and process control.
The student is capable of solving small to medium sized programming tasks in Python, in particular tasks related to data processing and analytics. The student can produce programs that are well-written, well-structured, and well-commented. Finally, the student knows how to execute scripts on a remote server, and navigate using a Unix command line interface on such a server.
After completing the course, the student is capable of solving the many small to medium size programming tasks that arise in Data Science disciplines, and is able to write well-structured and maintainable programs in Python. The student is also capable of running programs both locally and on remote servers, and be able to navigate in a Unix environment.
- can explain the differences between various data-types in Python and can select the relevant type for a given programming task
- can give a detailed description of conditionals and loops, and is able to explain how loops relate to the complexity of a program
- can motivate the concepts of function and module, and give examples of how these tools should be used to structure code
- can explain the basic concepts of Object Oriented Programming, and give examples of appropriate uses of classes and object
- can identify problems for which regular expressions are well suited, and is able to construct an appropriate regular expression for a given pattern matching problem
- can give examples of how to handle errors in a program
- is capable of independently finding online information about external Python modules, and applying this information to solve a specific task
This course is similar to NDAB21003U Python programmering til datavidenskab therefore it is not allowed to sign up for both courses.
- Practical exercises
- 7,5 ECTS
- Type of assessment
- Written examination, 4 hours under invigilation
- Exam registration requirements
Approval of 80% of the weekly exercises.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners.
Same as ordinary.
80% of the exercises must be handed in and approved no later than three weeks before the reexamination.
If ten or fewer students have signed up for re-exam, the type of assessment will be changed to 30 minutes oral exam, 30 minutes preparation, all aids allowed.
Criteria for exam assesment
See learning outcome
- Course code
- 7,5 ECTS
- 1 block
- Block 1
- Course capacity
The number of seats may be reduced in the late registration period
- Study Board for the Biological Area
- Department of Biology
- Department of Computer Science
- Faculty of Science
- Thomas Wim Hamelryck (8-776b6470686f757c43656c72316e7831676e)
- Wouter Boomsma (2-846f4d71763b78823b7178)