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: The Faculty Board of Science and Technology
- Revised: 2017-05-15
- Revised by: The Faculty Board of Science and Technology
- Applies from: Spring 2017
- Entry requirements:
- Responsible department: Department of Information Technology
Learning outcomes
To pass, 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 might include self-written MATLAB functions);
- structure and divide a computational problem into sub-problems, formulate an algorithm and implement the algorithm in MATLAB;
- in a short report explain and summarise solution methods and results in a lucid way.
Instruction
Lectures, workouts (problem solving classes), laboratory work, mini projects.
Assessment
Written examination (3 credits) and mini projects presented in writing (2 credits).
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: Spring 2017
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