Main field(s) of study and in-depth level:
Computer Science G2F
Explanation of codes
The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:
G1N: has only upper-secondary level entry requirements
G1F: has less than 60 credits in first-cycle course/s as entry requirements
G1E: contains specially designed degree project for Higher Education Diploma
G2F: has at least 60 credits in first-cycle course/s as entry requirements
G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
GXX: in-depth level of the course cannot be classified.
A1N: has only first-cycle course/s as entry requirements
A1F: has second-cycle course/s as entry requirements
A1E: contains degree project for Master of Arts/Master of Science (60 credits)
A2E: contains degree project for Master of Arts/Master of Science (120 credits)
AXX: in-depth level of the course cannot be classified.
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
The Faculty Board of Science and Technology
60 hp in science/technology including Scientific Computing, 5hp or Introduction to programming, scientific computing and statistics.
On completion of the course, the student should be able to:
indentify how programming and programming constructions, data types, modules and functions can be used to solve problems in enginnering or bioinformatics;
implement such solutions by writing Python programs with several interacting components;
use and describe the fundamental concepts module, function, class, object and related subconcepts:
use an integrated development environment for testing and debugging
The purpose of programming, programming in a context e.g. through applications. Translation between real-world problems and programs, the structure of a program. Write programs using functions, classes and built-in modules. The concepts module, function, class, object, scope. Control flow, data types, regular expressions, functions and modules in Python. Using packages such as numpy and scipy. Testing, debugging and documentation. Use an integrated development environment (IDE). The course is to a large extent application driven, where the learning mainly take place through assignments and a project.
Lectures, problem solving sessions/computer lab sessions, assignments, project.
Written exam (2hp). Assignments and projects (3hp).
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
The reading list is missing. For further information, please contact the responsible department.