Syllabus for Script Programming

Skriptprogrammering

Syllabus

  • 5 credits
  • Course code: 1TD328
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Computer Science A1N
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2017-03-07
  • Established by:
  • Revised: 2019-02-08
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 30, 2019
  • Entry requirements: Alt 1.120 credits. Computer Programming II or Bioinformatics - Starting Course (the latter can be taken at the same time).
    Alt 2.120 credits.Introduction to Bioinformatics (can be taken at the same time). Introduction to programming, scientific computing and statistics (can be taken at the same time).
    Alt 3.120 credits.Introduction to Bioinformatics (can be taken at the same time). 30 credits in mathematics together with 30 credits
    Computer Science.
    English language proficiency that corresponds to English studies at upper secondary (high school) level in Sweden ("English 6").
  • Responsible department: Department of Information Technology

Learning outcomes

On completion of the course, the student should be able to:

  • use scripting languages to solve scientific problems i.e. in bioinformatics or engineering;
  • use modules and write programs with several interacting components;
  • use an integrated development environment;
  • write shell scripts and combine shell scripts with Python

Content

The course is intended for students at the masters level interested in using scripting programming language for solving engineering problems, mainly related to bioinformatics and data handling. The course is to a large extent application driven, and the emphasis is on using a scripting language or shell scripts in combination with the scripting language.
Programming, debugging and execution in Python. Data types, regular expressions, functions and modules in Python. Coding for plotting of data (with matplotlib)  and management of numerical data (with numpy), and for analysis of genetic data. Use of a integrated development environment (IDE), and testing, debugging and documentation. Basic use of Linux via Bash (e.g. pipelines and commands like grep, awk and so forth). Shell scripts. 

Instruction

Computer labs. Programming assignments and feedback sessions linked to these assignments.

Assessment

Assignments and mini projects with oral presentation. 
 
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Other directives

The course cannot be included in the same degree as 1TD046 Programming, bridging course.

Reading list

Reading list

Applies from: week 30, 2019

Web based reference manuals and readings