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Introduction to Computational Thinking (ICT)

Vak
2019-2020

Description

Computational Thinking is an essential skill for the 21st-century. It is a method for problem solving, a prerequisite for learning to write computer scripts and to conduct computational drug research.

In this course, we will explore examples of computational thinking in drug research. We will start with a basic introduction to programming in R and follow this up with a computational view on mathematical equations, limits, partial derivatives and graphs of functions. We will then explore the use of linear models for statistical inference testing and how to apply this in R. A substantial part of the course will be hands-on-training in scripting your own computer programs in R using data sets that are relevant in drug research.

Course Objectives

The student is able to:

  • Solve mathematical equations, calculate limits and partial derivatives and draw graphs of functions

  • Analyse one-dimensional (1D) differential equations by pen and paper and interpret output from such analysis

  • Program an R-script to analyse mathematical equations including 1D differential equations

  • Program an R-script to format and analyze a (drug related) dataset and visualize the data

  • Peform statistical inference tests using linear models in R on data that often arises in drug research

Reading list

Literature will be provided during the course.

Coordinator

Dhr. Dr. J.B. Beltman

Mode of instruction

Practical course, consisting of: lectures, demonstrations, computer exercises, literature research and a group assignment.

Assessment method

Students will be assessed on the following modalities:

  • Weekly scripting tests (20%)

  • Group data-analysis assignment (20%)

  • Exam (60%)
    Total grade = 100%

Admission requirements & Registration

This course is mandatory for and restricted to students who do the Minor ‘Computational approach to Disease Signaling and Drug Targets’ (CADSDT; the entire Minor or only Part 1), the Minor ‘Modern Drug Discovery’ (MDD) and the Elective Module ‘DSDT’. The same admission criteria apply to this course as for the respective afore mentioned programs. Registration for the lectures and exam via uSis is mandatory.