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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

13.03.2023 - 27.08.2023

Timing

28.08.2023 - 17.12.2023

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
  • 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

Teaching languages
  • English
Seats

0 - 25

Teachers
  • Miika Aitomaa
Responsible person

Miika Aitomaa

Student groups
  • R54D21S
    Bachelor 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.