Course - Math for Biologists I – Linear Algebra - NEVR8012
NEVR8012 - Math for Biologists I – Linear Algebra
About
Examination arrangement
Examination arrangement: School exam
Grade: Passed / Not Passed
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| School exam | 100/100 | 4 hours | A |
Course content
Many fields within the Biological Sciences are becoming increasingly quantitative and interdisciplinary. This poses the double challenge of having a good understanding of the biological aspects of the problem under study, as well as of the mathematics used to analyze the acquired data and to develop models for it. The goal of this course is to introduce biologists to basic concepts in Linear Algebra that they will encounter in most of the analysis techniques and models they will employ in their research. The course will smoothly introduce the language of mathematics, with the aim of easing interdisciplinary communication. No previous knowledge of Linear Algebra is required, as we will start from the basics, namely: sets, vectors and matrices. We will then introduce the concepts of vector spaces and subspaces, while also covering linear combinations, bases, coordinates and dimensions. We will finish by discussing linear transformations, change of basis and eigendecomposition. We will integrate the acquired knowledge by introducing and discussing the technique of Principal Component Analysis.
Learning outcome
After completing the course the student will:
- Have been exposed to basic constructive mathematical reasoning, including a very limited exposure to mathematical proofs.
- Have a familiarity with fundamental and ubiquitous concepts from Linear Algebra including, but not limited to, the notion of a basis, coordinates and the dimension of a vector space, and an understanding of the concept of linear transformations, as well as eigenvalues and eigenvectors of a matrix.
- Be able to use this newfound knowledge to better understand the foundations of many analysis techniques widely employed in the Biological Sciences, such as Principal Component Analysis.
Learning methods and activities
Each class will be divided into a lecture and a practical session. The practical sessions will consist on solving exercises in order to assimilate the concepts introduced during the lectures. We will use the practical sessions to monitor the progress that the students make with the exercises. At the end of the course, and right before the exam, there will be a recap reserved for further discussion.
Compulsory assignments
- Exercises
Further on evaluation
The evaluation of the course will consist on a written exam, which will contain exercises similar to the ones discussed during the course. Additionally, students will be required to submit 4 short assignments throughout the course, which they will need to pass in order to be allowed to take the exam.
Compulsory activities from previous semester may be approved by the department.
Required previous knowledge
Admission requirements: The student must be either enrolled in a PhD programme, be a Medical student, be enrolled in the Student Research Programme or be enrolled in a MSc programme at NTNU. Candidates enrolled in the Master in Neuroscience programme at NTNU have to be assessed individually by the course coordinator.
Course materials
To be announced
No
Version: 1
Credits:
7.5 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: AUTUMN 2023
Language of instruction: English
Location: Trondheim
- Neuroscience
- Algebra
Department with academic responsibility
Kavli Institute for Systems Neuroscience
Examination
Examination arrangement: School exam
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD School exam 100/100 A INSPERA
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Room Building Number of candidates - Spring UTS School exam 100/100 A INSPERA
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"