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Mathematics for Intelligent Systems 7,5 Credits

Course Contents

The course contains elements from various fields of mathematics and mathematical statistics used when intelligent systems and machine learning are developed, used and analyzed.

The course includes the following elements:
- Vector and matrix calculations, linear maps Rn to Rm, eigenvectors and eigenvalues.
- Partial and total order relations, complexity, Big-O notation
- Partial derivatives, gradients, local convexity and extrema for smooth functions Rn to R
- Basic probability theory, Bayes’ theorem
- Discrete and continuous random variables
- Probability distributions, in particular binomial and normal distribution
- Point and interval estimation
- Hypothesis tests
- Single factor design experiments

Prerequisites

The applicant must hold the minimum of a bachelor’s degree (i.e the equivalent of 180 ECTS credits at an accredited university) with at least 90 credits in computer engineering, electrical engineering (with relevant courses in computer engineering), or equivalent. The bachelor’s degree should comprise a minimum of 15 credits in mathematics. Proof of English proficiency is required.

Level of Education: Master A1N
Course code/Ladok code: TMAR21
The course is conducted at: School of Engineering

Upcoming course occasions

Type of course
Program
Study type
Campus
Semester
Autumn 2021: Aug 23 - Oct 24
Rate of Study
100%
Language
English
Location
Jönköping
Time
Day
Course coordinator
Peter Olofsson
Examiner
Peter Olofsson
Tuition fees do NOT apply for EU/EEA citizens or exchange students
18750kr
Syllabus
HTML  PDF
Application code
HJ-T1311
Last modified 2021-03-30 14:42:29

Content updated