After completing the subject, the student will:
- have knowledge about different methods for selecting, retrieving and manipulating data;
- comprehend the influence of data selection and manipulation on subsequent analysis;
- comprehend the fundamental principles of selection, querying and programming that underlie the different tools presented in this course;
- be able to apply selected techniques on simulated and real data sources
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This is a computational thinking course focusing on data selection and data manipulation, and the underlying principles. That is, the primary goal is to make the students understand the abstractions that are necessary to achieve these goals. Their implementations by programming languages such as SQL and Python are the secondary goal.
The basic idea is that you first learn to select – and retrieve(!) – data from a wide variety of data sources. Unfortunately, such a selection is seldom in a form that allows you to analyze the data straight away; for example, because the data you need comes from a number of different data sources and needs to be glued together. In the second part, the student learns how manipulate the data in such a way that it does become amenable to analysis.
Part 1 Data Selection
- The logic of selection
- Selecting from structured data, e.g., using SQL
- Selecting from unstructured data, e.g., using regular expressions
Part 2 Data Manipulation
- The logic of manipulation
- Algorithms for data manipulation
- Manipulating data using Python
Part 3 Critical thinking in programming with data
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