Course code INF120

INF120 Programming and Data Processing

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Showing course contents for the educational year 2018 - 2019 .

Course responsible: Oliver Tomic
ECTS credits: 10
Faculty: Faculty of Science and Technology
Teaching language: NO
(NO=norsk, EN=Engelsk)
Teaching exam periods:
This course starts in the spring parallel. This course has teaching and evaluation during the spring parallel.
Course frequency: Annually
First time: Study year 2009-2010
Course contents:

The course will introduce you to programming and data processing with a focus on procedural programming in a high-level programming language. Specific topics are:

  • simple datatypes (numeric, boolean, character)
  • basic composite datatypes (strings, arrays, lists, dictionaries)
  • basic aspects of classes
  • control structures (branching, loops, list comprehensions)
  • functions and parameter exchange
  • recursive functions
  • reading from/writing to files
  • data analysis and -visualization
  • basic error handling
  • structuring of problem solutions
  • localization of errors in programs
  • editing, debugging

The course is based on the Python programming language.

Learning outcome:

After completing the course, you will know how to:

  • independently develop programs of limited complexity
  • read and understand programs at an equivalent level of complexity
  • analyse simple problems and implement algorithms to solve them
  • develop programs to analyze and visualize data
  • localise errors in programs
  • use basic programming tools

You will have acquired a basic knowledge of the higher level programming language used in the course. You will be able to evaluate the suitability of programs of limited complexity.

Learning activities:

Lectures: Presentation of the concepts behind programming, as well as the programming language. Analysis and solution of programming tasks.


Computer exercises: Students train concepts presented in the lecture through simple programming tasks solved in the computer lab with assistance.


Compulsory programming problems: By solving programming problems, the student practises analysing problems independently and implementing solutions as programs.


Independent study: Repetition of the material covered in the lectures and programming on your own.

Teaching support:
The teaching assistants will assist and support the students during the computer exercise sessions.Course room on Canvas.
Hans-Petter Langtangen, A Primer on Scientific Programming with Python, Springer Verlag. The course covers most of ch. 1-8 of the book  (3rd edition).
Recommended prerequisites:
Mandatory activity:
Students must get a sufficient number of obligatory exercises approved. More information will be given at the beginning of the course.
Final written examination based (3 hours).
Nominal workload:
300 hours: 52h lectures + 26h computer exercise + 52h independent work in the computer lab + 104h work on obligatory exercises + 52h self study + 14h exam preparation
Entrance requirements:
Special requirements in science
Type of course:
  • Lectures: 52h
  • Computer exercise sessions: 26h
The external and internal examiner jointly prepare the exam questions and the correction manual. The external examiner reviews the internal examiner's examination results by correcting a random sample of candidate¿s exams as a calibration according to the Department's guidelines for examination markings.
Allowed examination aids: A1 No calculator, no other aids
Examination details: One written exam: A - E / Ikke bestått