This course teaches students to:
- analyse problems from the perspective of solving them with a computer
- use the language Python to implement computer programs
- test computer programs to ensure their correct functioning
The course is presented as a series of iPython notebooks that will be provided on Blackboard. Students get an account on a server at the university, which makes all these notebooks available. The notebooks consist of instructions and exercises that can be done inside the notebooks or using a separate editor. In principle the notebooks contain all necessary information, and if they want, students can do the course completely without further instructions if they simply follow the notebooks.
The course will be evaluated on the basis of a midterm computer exam (30%) and a final computer exam (70%); the weighted average grade of these two components needs to be a passing grade. Every week, take-home exercises will be handed out, for which the students should create solutions in the form of programs. The main goal of the take-home assignments is to assure that the students keep working at a steady pace, and for the instructor to see where there are still problems.
None, though an aptitude for abstract thinking is helpful.
The growth of the internet and associated services has enabled the investigation of large text and data corpora. The processing and analysis of these corpora using statistical methods is difficult because of the enormous volumes of data. A computer is a powerful tool to perform such analyses. This course provides students with practical skills to use computers as general tools for working with data sets and solving quantitative problems. The skills acquired are particularly helpful for reducing the time spent on data analysis in research (e.g., for Master thesis work).|
Students will learn the basics of the computer language Python, which is suitable for quickly creating short programs to process texts and data sets. Python is a language that is easy to use by novices, yet sufficiently powerful to create programs of any size and complexity. Moreover, while being a complete, free-to-use, flexible, operating-system-independent language of its own, it also constitutes a strong basis to learn any other computer language from.
- Students who completed the course 827104 Basic Programming, 822188 Data Structures and Algorithms or the third-year course 822235 Seminar Data Processing, or 827154 Advanced Programming, must choose a different OZV/Research Skills module, as this course does not offer anything new to them.
- Students of the mastertrack DSBG, who already passed 827104 Basic Programming, 822188 Data Structure and Algorithms, 822235 Seminar Data Processing or 827154 Advanced Programming CIS, have to file a request to the Board of Examiners in order to be assigned an alternative Research Skills course.