MM555: Mathematics for Molecular Bioscience, Biomedicine and Chemistry

Study Board of Science

Teaching language: Danish or English depending on the teacher, but English if international students are enrolled
EKA: N300016112, N300016102
Assessment: Second examiner: None, Second examiner: Internal
Grading: Pass/Fail, 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Bachelor

STADS ID (UVA): N300016101
ECTS value: 5

Date of Approval: 25-04-2019


Duration: 1 semester

Version: Archive

Entry requirements

The course cannot be chosen by students, who have passed FF502, FF506, MM536.

However, this course can only be taken if it:

  1. is a constituent part of your programme 
  2. is a specified recommendation for elective ECTS in your programme
  3. is part of a specified transitional arrangement ('overgangsordning') for a course you have not yet passed

Academic preconditions

Students taking the course are expected to:

  • Have knowledge of mathematics corresponding to the A-level in the Danish high school system.
  • Be able to use the techniques covered in the high school A-level curriculum.

Course introduction

The aim of the course is to introduce the student to the central tools in calculus to be used in the degrees of BMB, biomedicine and chemistry, which use will be illustrated in later courses of the study.

These tools will give the student the necessary skills to:

  1. Argue in a logical and rigorous manner.
  2. Understand how physical, chemical and biological phenomena can be described using mathematics.
  3. Construct mathematical models describing phenomena occurring in the natural sciences.
In relation to the competence profile of the degree it is the explicit focus of the course to:
  • Give the competence to understand and construct mathematical models.
  • Give the competence to argue rigorously.
  • Give skills to argue in a general scientific context.
  • Give skills to work independently with mathematics.
  • Give knowledge and understanding of basic calculus.
  • Give knowledge and understanding of the interplay between mathematics and the natural sciences.

Expected learning outcome

The learning objectives of the course are that the student demonstrates the ability to:

  • Argue in a logical and rigorous manner.
  • Understand and work with the mathematical theories introduced in the course.
  • Construct simple mathematical models describing phenomena occurring in the natural sciences.

Content

The following main topics are contained in the course:

  • Basic function theory
  • Limits
  • Taylor polynomials
  • Complex numbers and polar coordinates
  • Differentiation and integration of functions in one variable
  • Extreme values of functions
  • Differential equations of first and second order
  • Functions in several variables and partial derivatives

Literature

See itslearning for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

Autumn

Tests

Mandatory assignments

EKA

N300016112

Assessment

Second examiner: None

Grading

Pass/Fail

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value

2

Additional information

The examination form for re-examination may be different from the exam form at the regular exam.

Exam element b)

Timing

January

Tests

Written exam

EKA

N300016102

Assessment

Second examiner: Internal

Grading

7-point grading scale

Identification

Student Identification Card

Language

Normally, the same as teaching language

Duration

2 hours

Examination aids

A closer description of the exam rules will be posted n itslearning.

ECTS value

3

Additional information

The examination form for re-examination may be different from the exam form at the regular exam.

Indicative number of lessons

68 hours per semester

Teaching Method

In order to enable students to achieve the learning objectives for the course, the teaching is organised in such a way that there are 58 lectures, class lessons, etc. on a semester.
These teaching activities are reflected in an estimated allocation of the workload of an average student as follows:

  • Intro phase (lectures, class lessons) - 26 hours
  • Training phase: 28 hours
  • Study phase: 14 hours

During the study phase students are expected to:

  • Work with the new concepts and terms introduced.
  • Increase their understanding of the topics covered during the lectures.
  • Solve relevant exercises.

Teacher responsible

Name E-mail Department
David Kyed dkyed@imada.sdu.dk Analysis

Timetable

Administrative Unit

Institut for Matematik og Datalogi (matematik)

Team at Educational Law & Registration

NAT

Offered in

Odense

Recommended course of study

Profile Education Semester Offer period