Syllabus for Scientific Computing KF
Beräkningsvetenskap KF
A revised version of the syllabus is available.
Syllabus
- 5 credits
- Course code: 1TD399
- Education cycle: First cycle
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Main field(s) of study and in-depth level:
Computer Science G1N,
Technology G1N,
Mathematics G1N
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:
First cycle
- 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
Second cycle
- 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
- Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Established: 2011-03-10
- Established by:
- Revised: 2019-02-13
- Revised by: The Faculty Board of Science and Technology
- Applies from: Autumn 2019
- Entry requirements:
- Responsible department: Department of Information Technology
Learning outcomes
On completion of the course, the student should be able to
- describe and perform tasks in connection to the key concepts covered in the course;
- explain the idea behind and apply the algorithms covered in the course;
- explore properties for numerical methods and mathematical models by using the analysis methods covered in the course;
- explain the results when running a MATLAB program, and describe a problem with an algorithm or a programming code in MATLAB, which for instance might include self-written MATLAB functions;
- structure and divide a computational problem into sub-problems, formulate an algorithm and implement the algorithm in MATLAB;
- solve smaller calculation problems in a structured manner and implement in MATLAB.
Instruction
Lectures, workouts (problem solving classes), laboratory work, assignments and mini projects.
Assessment
Written examination (3 credits). Individual assignments, workouts and mini project (2 credits).
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.
Syllabus Revisions
- Latest syllabus (applies from Autumn 2020)
- Previous syllabus (applies from Autumn 2019)
- Previous syllabus (applies from Autumn 2017)
- Previous syllabus (applies from Spring 2017)
- Previous syllabus (applies from Autumn 2015)
- Previous syllabus (applies from Autumn 2013)
- Previous syllabus (applies from Spring 2011)
- Previous syllabus (applies from Autumn 2010, version 2)
- Previous syllabus (applies from Autumn 2010, version 1)
Reading list
Reading list
Applies from: Autumn 2019
Some titles may be available electronically through the University library.
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Chapra, Steven C.
Applied numerical methods with MATLAB for engineers and scientists
3. international ed.: Boston: McGraw-Hill Higher Education, 2012
Mandatory