Linear AlgebraLaajuus (5 cr)
Code: R504D58
Credits
5 op
Teaching language
- English
Objective
The student learns fundamental mathematical concepts, principles, tools (including computing environments) and terminology for professional studies.
Content
- Mathematical objects: scalars, vectors, matrices and tensors
- Basic matrix operations
- Special type of matrices and vectors
- Systems of linear equations
- Determinants
- Analytic geometry; inner and outer products, projections
- Vector spaces and linear mappings
- Linear dependence, span
- Linear regression
Assessment criteria, satisfactory (1)
The student knows the concepts of linear algebra and is able to solve basic problems.
Assessment criteria, good (3)
The student understands the concepts of linear algebra and is able to solve varied problems related to applications of linear algebra.
Assessment criteria, excellent (5)
The student understands the concepts of linear algebra and is able to apply methods of linear algebra in solving and handling new types of problems.
Enrollment
15.05.2024 - 25.08.2024
Timing
26.08.2024 - 10.11.2024
Credits
5 op
Mode of delivery
Contact teaching
Teaching languages
- English
Seats
0 - 30
Degree programmes
- Machine Learning and Data Engineering
Teachers
- Miika Aitomaa
Responsible person
Miika Aitomaa
Student groups
-
R54D23SBachelor of Engineering, Machine Learning and Data Engineering (full time studies), 2023
Objective
The student learns fundamental mathematical concepts, principles, tools (including computing environments) and terminology for professional studies.
Content
- Mathematical objects: scalars, vectors, matrices and tensors
- Basic matrix operations
- Special type of matrices and vectors
- Systems of linear equations
- Determinants
- Analytic geometry; inner and outer products, projections
- Vector spaces and linear mappings
- Linear dependence, span
- Linear regression
Location and time
Autumn term 2024, Lapland University of Applied Sciences, Rantavitikka campus (Rovaniemi, Jokiväylä 11)
Materials
Study material is available as an eBook and on the Moodle learning platform.
Teaching methods
Lessons and exercises
Exam schedules
The number and date of exams will be agreed on during the course. Resit is possible by the end of the next term.
Completion alternatives
Studying independently is possible. All exercises must be returned in time to be evaluated.
Evaluation scale
H-5
Assessment criteria, satisfactory (1)
The student knows the concepts of linear algebra and is able to solve basic problems.
Assessment criteria, good (3)
The student understands the concepts of linear algebra and is able to solve varied problems related to applications of linear algebra.
Assessment criteria, excellent (5)
The student understands the concepts of linear algebra and is able to apply methods of linear algebra in solving and handling new types of problems.
Assessment methods and criteria
Evaluation is based on exercises and/or tests and/or exams. Students will also participate on a project, where linear algebra is integrated. The emphasis on these will be agreed upon at the beginning of the course.
Assessment criteria, fail (0)
Student doesn't meet the basic requirements of grade 1.
Assessment criteria, satisfactory (1-2)
Student understands basic concepts of linear algebra (vectors and matrices) and is capable of solving basic exercises, such as basic vector and matrix calculus and systems of two equations.
Assessment criteria, good (3-4)
Student understands more complicated concepts of linear algebra, such as linear dependency and independency, vector spaces, projections and transformations, determinants, and is capable of solving versatile exercises, such as inner and outer products, matrix equations and solving systems of linear equations. Student uses correct mathematical language and can create logical solutions.
Assessment criteria, excellent (5)
Student is capable of applying concepts of linear algebra to new problems and solve them in exact mathematical language.
Enrollment
13.03.2023 - 27.08.2023
Timing
28.08.2023 - 17.12.2023
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- English
Seats
0 - 30
Degree programmes
- Machine Learning and Data Engineering
Teachers
- Miika Aitomaa
Responsible person
Miika Aitomaa
Student groups
-
R54D22S
Objective
The student learns fundamental mathematical concepts, principles, tools (including computing environments) and terminology for professional studies.
Content
- Mathematical objects: scalars, vectors, matrices and tensors
- Basic matrix operations
- Special type of matrices and vectors
- Systems of linear equations
- Determinants
- Analytic geometry; inner and outer products, projections
- Vector spaces and linear mappings
- Linear dependence, span
- Linear regression
Location and time
Autumn term 2023, Lapland University of Applied Sciences, Rantavitikka campus (Rovaniemi, Jokiväylä 11)
Materials
Study material is available as an eBook and on the Moodle learning platform.
Teaching methods
Lessons and exercises
Exam schedules
The number and date of exams will be agreed on during the course. Resit is possible by the end of the next term.
Completion alternatives
Studying independently is possible. All exercises must be returned in time to be evaluated.
Evaluation scale
H-5
Assessment criteria, satisfactory (1)
The student knows the concepts of linear algebra and is able to solve basic problems.
Assessment criteria, good (3)
The student understands the concepts of linear algebra and is able to solve varied problems related to applications of linear algebra.
Assessment criteria, excellent (5)
The student understands the concepts of linear algebra and is able to apply methods of linear algebra in solving and handling new types of problems.
Assessment methods and criteria
Evaluation is based on tests and/or exams, exercises, project. The emphasis on these will be agreed upon at the beginning of the course.
Assessment criteria, fail (0)
Student doesn't meet the basic requirements of grade 1.
Assessment criteria, satisfactory (1-2)
Student understands basic concepts of linear algebra and is capable of solving basic exercises.
Assessment criteria, good (3-4)
Student understands more complicated concepts of linear algebra and is capable of solving versatile exercises. Student uses correct mathematical language and can create logical solutions.
Assessment criteria, excellent (5)
Student is capable of applying concepts of linear algebra to new problems and solve them in exact mathematical language.
Enrollment
14.03.2022 - 29.08.2022
Timing
03.09.2022 - 18.12.2022
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- English
Seats
0 - 25
Teachers
- Miika Aitomaa
Responsible person
Miika Aitomaa
Student groups
-
R54D21SBachelor of Engineering, Machine Learning and Data Engineering (full time studies), 2021
Objective
The student learns fundamental mathematical concepts, principles, tools (including computing environments) and terminology for professional studies.
Content
- Mathematical objects: scalars, vectors, matrices and tensors
- Basic matrix operations
- Special type of matrices and vectors
- Systems of linear equations
- Determinants
- Analytic geometry; inner and outer products, projections
- Vector spaces and linear mappings
- Linear dependence, span
- Linear regression
Location and time
Autumn term 2022, Lapland University of Applied Sciences, Rantavitikka campus (Rovaniemi, Jokiväylä 11)
Materials
Study material is available on Moodle learning platform.
Teaching methods
Lessons and exercises
Exam schedules
The number and date of exams will be agreed during the course. Resit is possible by the end of the next term.
Completion alternatives
Studying independently is possible. All exercises must be returned in time to be evaluated.
Evaluation scale
H-5
Assessment criteria, satisfactory (1)
The student knows the concepts of linear algebra and is able to solve basic problems.
Assessment criteria, good (3)
The student understands the concepts of linear algebra and is able to solve varied problems related to applications of linear algebra.
Assessment criteria, excellent (5)
The student understands the concepts of linear algebra and is able to apply methods of linear algebra in solving and handling new types of problems.
Assessment methods and criteria
Evaluation is based on tests, exams and exercises. Emphasis of these will be agreed on in the beginning of the course.
Assessment criteria, fail (0)
Student doesn't meet the basic requirements of grade 1.
Assessment criteria, satisfactory (1-2)
Student understands basic concepts of linear algebra and is capable of solving basic exercises.
Assessment criteria, good (3-4)
Student understands more complicated concepts of linear algebra and is capable of solving versatile exercises.
Assessment criteria, excellent (5)
Student is capable of applying concepts of linear algebra to new problems and solve them.