Study Guide

Objective

The student learns fundamental mathematical concepts, principles, tools and terminology to be applied in professional studies.

Content

- Basics of logic and set theory
- Expressions, equations, inequality
- Functions
- Geometry; 2D, 3D
- Trigonometry

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 algebra, geometry and trigonometry, and is able to solve basic problems.

Assessment criteria, good (3)

The student understands the concepts of algebra, geometry and trigonometry, and is able to solve varied problems related to applications of algebra, geometry and trigonometry.

Assessment criteria, excellent (5)

The student understands the concepts of algebra, geometry and trigonometry, and is able to apply methods of algebra, geometry and trigonometry in solving and handling new types of problems.

Assessment methods and criteria

Evaluation is based on exercises and tests and/or exams . The emphasise 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 subject matter, such as basic calculus of fractions, powers, roots and polynomials. Student is capable of solving basic exercises such as linear equations and quadratic equations, and can solve a missing side and angle of a right triangle using trigonometry and Pythagorean Theorem.

Assessment criteria, good (3-4)

Student understands more complicated concepts of subject matter, such as the properties of quadratic functions and solid geometry. Student is capable of solving versatile exercises such as factoring, inequalities and versatile geometrical problems. Student uses correct mathematical language and can create logical solutions.

Assessment criteria, excellent (5)

Student is capable of applying concepts of subject matter to new problems and solve them in exact mathematical language.

Objective

The student knows and can apply the primary data structures and algorithms. The student can compare their efficiency and complexity.

Content

- Algorithmic complexity and evaluation of the performance of algorithms: the Big O notation.
- The primary data structures and their implementations: arrays, linked lists, stacks, queues, graphs, binary trees.
- The primary algorithms and their implementations: recursion, searching and sorting.

Location and time

Computer labs at Rantavitikka Campus in the autumn term 2024.

Materials

Lecture materials, examples, exercises and assignments in Moodle workspace and/or OneDrive.



Course book

Carrano F. & Henry T. 2018. Data Structures and Abstractions with Java. 5th Edition. Pearson

Recommended reading

Goodrich M. T. & al. 2014. Data Structures and Algorithms in Java: International Student Version. 6th Edition.

Wiley Weiss M. 2012. Data Structures and Algorithm Analysis in Java: International Edition. 3rd Edition. Pearson Education

Teaching methods

Lectures and exercises, assignment and self-supervised work.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student can compare the complexity of algorithms and apply some basic data structures and algorithms.

Assessment criteria, good (3)

The student can compare the complexity of algorithms and apply a variety of data structures and algorithms. The student is familiar with the internal implementation of the most common data structures and algorithms.

Assessment criteria, excellent (5)

The student can evaluate the complexity of algorithms and apply a wide variety of data structures and algorithms. The students is familiar with the internal implementation of the primary data structures and algorithms. The student can choose the most effective data structures and algorithms for a given task.

Objective

This course orientates students to electronics lab work. The course introduces students to electronic components, test setups, the basics of device construction and the use of measuring equipment as part of electronics analysis and design. The course is intended for computer science students whose studies do not actually aim at electronics design. The course also introduces microcontrollers (Micro Controller Unit, MCU) and their use in sensor data acquisition and actuator control.

Content

1. Intro to the Course
2. Electrical Safety
3. Basics of Electric Circuits
4. Components in Electronics
5. Signals in Electronics
6. Soldering in Electronics
7. Soldering exercises
8. Measurements in Practice
9. Electronics measurements in practice exercise
10. Computer Aided Engineering (CAE) in electronics
11. Microcontrollers & Sensors in IoT

Location and time

The introductory lectures of the course will be held on week 36. The course includes (4 x 8 + 4) hours of lessons per week, in addition to self-study. There will be no lessons held during the weeks 37, 41. and 42. and the course ends on week 50. The teacher will grade the course by December the 31st at the latest. The Lectures and labs will be held from week 36 to week 43.

Materials

All study material needed for the study course is offered in the study course's workspace.

Teaching methods

The course consists of classroom lessons and laboratory work. The course involves independent work and reporting.

Exam schedules

The course is completed with exercises and reports that are scored. The course does not include an exam, except in specially agreed special cases.

Completion alternatives

For justified reasons, the course can be completed with a closed exam, the content of which is agreed with the individual lecturer.

Content scheduling

A list of topics and techniques covered during the Course:

Labs on-site (from week 37 to week 43)

1. wk. 37. 4th Sept. 2023 08:15 - 16:00
- Intro to the Course.
- Components in Electronics
- Soldering in Electronics. (week assignment #1, 10 pts max.)

2. wk. 38. 20th Sept. 2023 08:15 - 16:00
- Electrical Safety (week assignment #2, 10 pts max.)

3. wk. 39. 29th Sept. 2023 08:15 - 16:00
- Basics Measurements in Electronics (week assignment #3, 10 pts max.)

4. wk. 40. 3rd Oct. 2023 08:15 - 16:00
- Computer Aided Engineering (CAE) in Electronics (week assignment #4, 10 pts max.)

5. wk. 43. (week assignment #5, 10 pts max.)
- AC and distortion analysis exercise. (week assignment #5, 10 pts max.)

Project work (from week 43 to week 49)

Project work report about electronics in Your project (Project report, 10 pts max)

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is able to analyze the basic currents, voltages and powers of an electronic circuit. The student masters the properties of electronic components such as passive components and semiconductors. The student recognizes electronic components such as diodes and transistors as well as integrated circuits such as operational amplifiers and is able to analyze their basic connections.

Assessment criteria, good (3)

In addition to basic analyzes such as current voltages and powers, the student is able to perform frequency level analyzes. The student masters the basics of the analysis of dynamic properties such as delays and responses.

Assessment criteria, excellent (5)

The student is able to choose the connection of analog electronics and analyze its suitability for the current design problem. The student’s design and analysis skills are sufficient to apply the connections.

Assessment methods and criteria

The assessment is based on week assignments and lab reports.

Week assignments are scored 0 to 10 pts.

Participation in laboratory work is assessed with a grade of:
0 pts - did not participate
1 pts - participated
2 pts - returned the weekly asssignment report

The returned reports of the lab reports are evaluated from 0 to 10 pts.

Evaluation scale Note! Rating scale reduced slightly due the fact there is only 5 assignments which weight is big to compared to assignments, also pts. limits was decreased 1pt:

0 - 15 Failed
16 - 21 Grade 1
22 - 28 Grade 2
29 - 34 Grade 3
35 - 41 Grade 4
42 - 50 Grade 5

Assessment criteria, satisfactory (1-2)

The student is able to analyze the basic currents, voltages and powers of an electronic circuit. The student masters the properties of electronic components such as passive components and semiconductors. The student recognizes electronic components such as diodes and transistors as well as integrated circuits such as operational amplifiers and is able to analyze their basic connections.

Assessment criteria, good (3-4)

In addition to basic analyzes such as current voltages and powers, the student is able to perform frequency level analyzes. The student masters the basics of the analysis of dynamic properties such as delays and responses.

Assessment criteria, excellent (5)

The student is able to choose the connection of analog electronics and analyze its suitability for the current design problem. The student’s design and analysis skills are sufficient to apply the connections.

Objective

The student learns different concepts of entrepreneurship, its importance for economies, and the people involved.

The student learns business idea development that is explored from a theoretical viewpoint as well as from a practical viewpoint.

The student learns to identify, develop, and assess future-oriented business opportunities and ideas.

The student is familiar with business startup theories and processes.

The student can prepare a business plan with its calculations and present the businesses successfully.

The student understands sustainable development, social responsibility and circular economy as part of business and learns about their impact on business models.

Content

- Tools and techniques related to developing a business idea.
- Analyzing a business case and critically assess the quality of entrepreneurial strategies and tactics based on theoretical and practical insights.
- Key theoretical approaches associated with business idea development.
- Launching a start-up company
- Sustainable development, social responsibility and circular economy as part of business and their impact on business models

Location and time

Autumn-24. Jokiväylä campus Rovaniemi.
Implementation period 2.9 - 13.10.2024

Materials

The material shared by the teacher in the Moodle workspace

Teaching methods

Lectures and group work.

Exam schedules

No exam during the course

Content scheduling

Themes in the course
- Entrepreneurship
- Businessplan
- Marketing and customer service
- Finance and financial management

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student understands different concepts of entrepreneurship and its importance for economies.

The student can prepare a business plan.

Assessment criteria, good (3)

The student can utilize business start-up theories and processes.

Assessment criteria, excellent (5)

The student can utilize future-oriented business opportunities and ideas to develop a business plan. The student is familiar with business start-up theories and processes.

Assessment methods and criteria

Successful completion of assigned tasks is required for all tasks.

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.

Objective

Theme: communication in working life

The student is able to communicate interactively in different working life situations in the field of ICT. The student can prepare and give a professional presentation, make phone calls and use e-mail in an appropriate and professional manner. The student can participate meetings and negotiations and write related documents. The student can tell about their education and discuss topics in the field of ICT. The student can use appropriate style in different situations and consider cultural differences in communication.

Proficiency level B2

Content

Telephone and e-mail communication
Professional presentation and presentation skills
Work of an ICT engineer
Applying for a job, CV, job interview
Meeting terminology
Professional language, terminology and texts
Speaking, writing and listening tasks

Location and time

Autumn 2024, Rovaniemi

Materials

Study material available on Moodle.

Teaching methods

Contact lessons, independent studying

Exam schedules

Exam dates will be decided during the course.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student communicates understandably in English in different working life situations both in writing and speech. The student is able to apply for work using English and knows the language of formal meetings, as well as ICT related terminology.

Assessment criteria, good (3)

The student is able to communicate fairly fluently in English both in speech and in writing and is able to use appropriate style in different situations. The student knows rather advanced terminology of working life and information and communication technology. The student is able to represent their employer in various situations.

Assessment criteria, excellent (5)

The student communicates fluently both in speech and in writing in English using appropriate style. The student uses language structures flawlessly and pronounces fluently and clearly. The student can use correct terminology in various working life situations and masters the terminology of information and communication technology. The student is able to take into account multicultural aspects in communication.

Assessment methods and criteria

Assessment is based on the student's active participation in contact lessons. The required assignments must be done and there is also a written exam. Oral skills will be assessed continuously during the study unit.
The assessment is based on the Common European framework, skill level B2.

Assessment criteria, fail (0)

Student does not fulfill the requirements.

Assessment criteria, satisfactory (1-2)

The student can represent his or her company and present products and work in projects if given enough time and tools to prepare beforehand. The student can use the basic terminology of ICT, uses the basic structures of English mainly correctly and pronounces English understandably.

Assessment criteria, good (3-4)

The student is able to represent own company and products fluently in English using appropriate style. The student uses versatile language structures and vocabulary and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication

Assessment criteria, excellent (5)

The student can represent own company and present products very fluently and accurately using appropriate style. The student uses language structures flawlessly and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication.

Objective

Theme: communication skills in ICT business

The student is able to manage in demanding working life situations in English taking cultural differences into consideration and using appropriate style. The student is able to follow development in ICT domain. The student can represent their employer or company at trade fairs and other occasions and present state-of-the-art ICT technology in English.

Proficiency level B2

Content

Professional language in ICT
ICT companies, types of companies
Representing a company and its products
Negotiations
Trade fairs
ICT projects
Speaking, writing and listening tasks

Location and time

Autumn 2024

Materials

Material available on Moodle

Teaching methods

Contact lessons, independent studying

Exam schedules

The schedule for exams will be decided during the study unit.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student communicates understandably in English about the topics of working life and information and communication technology. The student knows the basic terminology and types of businesses. The student can represent their employer provided that there is a chance to prepare beforehand.

Assessment criteria, good (3)

The student is able to communicate fairly fluently in English both in speech and in writing. The student knows rather advanced terminology of working life and information and communication technology. The student is able to represent their employer in various situations.

Assessment criteria, excellent (5)

The student communicates fluently both in speech and in writing in English. The student uses the terminology of various working life situations and information and communication technology skillfully and is able to take into account multicultural aspects in communication.

Assessment methods and criteria

Assessment is based on student's activity and written and oral exams.

Assessment criteria, fail (0)

Student doesn't fulfill the requirements.

Assessment criteria, satisfactory (1-2)

The student can represent his or her company and present products and work in projects if given enough time and tools to prepare beforehand. The student can use the basic terminology of ICT, uses the basic structures of English mainly correctly and pronounces English understandably.

Assessment criteria, good (3-4)

The student is able to represent their own company and products fluently in English using appropriate style. The student uses versatile language structures and vocabulary and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication.

Assessment criteria, excellent (5)

The student can represent their own company and present products very fluently and accurately using appropriate style. The student uses language structures flawlessly and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication.

Objective

Theme: Written Communication in Engineering

The student can write various kinds of documents and texts in the field of ICT using appropriate style and terminology and grammatically correct language. The student knows the principle rules of akademic writing. The student knows the purchasing process of a technology company and related documents and terminology.

Proficiency level B2

Content

Purchasing process of a technology company
Business documents
Academic writing
Writing a professional report
Speaking, writing and listening tasks

Location and time

Rovaniemi, spring 2025

Materials

Moodle material

Professional literature

Teaching methods

Contact lessons

Exam schedules

Will be decided at the beginning of the study unit.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student knows the purchasing process of a technology company and the related business documents. The student knows the basics of academic writing and can draw up understandable documents using helping tools.

Assessment criteria, good (3)

The student knows the purchasing process of a technology company and the related business documents and appropriate terminology and phrases. The student knows the principle rules of academic writing and is able to prepare different kinds of documents using appropriate style.

Assessment criteria, excellent (5)

The student knows the purchasing process of a technology company and related documents. The student can draw up related documents using appropriate terminology and phrases and grammatically flawless language. The student knows and understands the rules of academic writing and is able to write grammatically correct academic text.

Assessment methods and criteria

Assessment is based on the European language assessment framework level B2 and the course assignments.

Assessment criteria, fail (0)

The student does not do the course assignments.

Assessment criteria, satisfactory (1-2)

The student knows the basics of academic writing and can draw up understandable documents using helping tools.

Assessment criteria, good (3-4)

The student knows the rules of academic writing and is able to prepare different kinds of documents using appropriate style.

Assessment criteria, excellent (5)

The student can draw up documents using appropriate terminology and phrases and grammatically flawless language. The student knows and understands the rules of academic writing and is able to write grammatically correct academic text.

Objective

The student is able to carry out a development project that includes practical machine learning. The student is able to apply appropriate modern tools and methods to development work. The student is able to make decisions in unforeseen situations and utilize various communication channels and tools in the external and internal communication of the project. The student is capable of multicultural collaboration.

Content

- A multicultural work community
- Automation Testing / DevOps

Location and time

Classes and workshops take place on the Rovaniemi Jokiväylä campus in the scheduled classroom. Additional team meetings will be arranged as needed.

Materials

Selected research articles and online resources provided throughout the course.

Reading:

Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto. Second Edition, MIT Press, Cambridge, MA, 2018

Link: http://incompleteideas.net/book/the-book-2nd.html

Deep Learning (Adaptive Computation and Machine Learning series), An MIT Press book, Ian Goodfellow and Yoshua Bengio and Aaron Courville

Link: https://www.deeplearningbook.org/

Teaching methods

The study module employs project-based learning, where students collaborate in teams to develop practical machine learning and AI solutions utilizing DevOps principles and methods. Regular workshops, seminars, and mentoring sessions will support the project work. Active participation and engagement in all activities are expected.

Employer connections

The study module aims to include collaboration with industry partners, offering students real-world problems to solve. This provides practical experience and networking opportunities within the field.

Exam schedules

There are no traditional exams. Assessment is continuous and based on project milestones, presentations, and final deliverables. Opportunities for resubmission will be provided for components that do not meet the required standards.

International connections

International students are welcome, and all course activities are conducted in English.

Completion alternatives

Alternative completion methods may be applicable through the process of identification and recognition of acquired competencies.

Content scheduling

1. Introduction, team formation, project topic selection
2. Project planning, literature review, initial development
3. Automation and testing
4. Mid-project reviews, implementation
5. Refinement, troubleshooting, preparation for final presentation
6. Final presentations, submission of project reports

Further information

Students are expected to maintain regular communication with instructors and team members. All resources and announcements will be available on the study module's online platform (Moodle).

Evaluation scale

H-5

Assessment methods and criteria

Project Development (50%): Quality, innovation, and functionality of the final product.
Team Collaboration (20%): Contribution to team efforts and effective communication.
Presentations (15%): Clarity, professionalism, and ability to articulate project details.
Documentation (15%): Completeness, clarity, and organization of reports and code documentation.

Final Seminar, Project Reporting and Peer Reviews are essential parts of the assessment.

Grading of 0 to 5 is used where 0 is Fail and 5 is Excellent

Assessment criteria, satisfactory (1-2)

Basic machine learning and AI concepts are implemented, resulting in a product with some functionality. Contribution to team efforts is observable but may be inconsistent. Presentations cover essential aspects of the project but may lack clarity or depth. Documentation provides a basic overview but might be lacking in detail or organization.

Assessment criteria, good (3-4)

Machine learning and AI concepts are applied effectively, producing a functional product with moderate technical complexity. Active participation in team activities is demonstrated, contributing positively to the team's objectives. Presentations are clear and professional, conveying technical details adequately. Documentation is well-organized and offers a good understanding of the project's technical aspects.

Assessment criteria, excellent (5)

Advanced machine learning and AI techniques are applied proficiently, resulting in a highly functional and innovative product. Significant contributions to the team are made, potentially taking on coordination roles and promoting effective collaboration. Presentations are professional and clear, thoroughly explaining the project's technical components. Documentation is comprehensive and well-structured, providing detailed insights into the project's development and implementation.

Objective

The student learns fundamental mathematical concepts, principles, tools (including computing environments) and terminology of statistics, probability and optimization for professional studies.

Content

Theory of statistics and probability
- Numerical and graphical description of data
- Probability, probability rules and theorems, probability distribution
- Modeling, parameter estimation
- Model selection, decision theory
- Analysis task types

Optimization, differential calculus and numerical computation
- Objective function
- Critical points, extrema
- Types of optimization problems
- Limit, derivative, partial derivative, differentiation rules
- Iterative gradient-based optimization methods, derivative-free methods

Location and time

Spring term 2025, 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)

Assessment criteria - grade 1
The student knows the concepts of probability, statistics, and optimization and is able to solve basic problems.

Assessment criteria, good (3)

Assessment criteria - grade 3
The student understands the concepts of probability, statistics, and optimization and is able to solve varied problems related to applications of probability, statistics, and optimization.

Assessment criteria, excellent (5)

The student understands the concepts of probability, statistics, and optimization and is able to apply methods of probability, statistics, and optimization in solving and handling new types of problems.

Assessment methods and criteria

Evaluation is based on exercises (homework) and/or exams. 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 knows the basic concepts of probability, statistics, and optimization, and is able to solve basic problems.

Assessment criteria, good (3-4)

Student understands more complicated concepts of probability, statistics, and optimization, 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 probability, statistics, and optimization to new problems and solve them in exact mathematical language.

Objective

The student learns to understand business operations (B2B), supply and distribution networks, customer value, and profitability. The student learns about the current and the future management and leadership. The student learns Lean Management principles in a business or an organization with continuous improvement with small and incremental changes to improve the value of products or services (with improved quality) and decrease wastes, defects, and costs. The student understands the impact of sustainable development and circular economy on industrial engineering.

Content

- How to run business operations.
- Lean management principles; factors contributing to organizational waste; examining ways to eliminate waste; developing & implementing improved organizational processes, for significant impact to the company’s bottom line.
- How lean management today represents a profound change in the competitive business culture and a leading indicator of excellence in the organization
- Basic principles of lean management strategy, in POM (production and operations management) & supply chain management
- How by implementing lean management organizations can improve product & processes without adding any more money, people, equipment, inventory, or space and aim for perfection.

Location and time

Autumn-24. Jokiväylä campus Rovaniemi.
Implementation period 2.9 - 13.10.2024.

Materials

The material shared by the teacher in the Moodle workspace.

Teaching methods

Lectures and group work.

Exam schedules

No exam during the course.

Content scheduling

In the course, we examine the effects of the Lean management method in relation to the following issues.
- Production management
- Quality management
- Logistics
- Lean management

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student knows principles of business operations and Lean management.

Assessment criteria, good (3)

The student can utilize the information of current business operations to improve quality and decrease waste, defects and costs.The student knows the Lean Management principles.

Assessment criteria, excellent (5)

The student understands business operations and can show how by implementing lean management organizations can improve product & processes without adding any more money, people, equipment, inventory or space and aim for perfection.

Assessment methods and criteria

Successful completion of assigned tasks is required for all tasks.

Assessment criteria, satisfactory (1-2)

Knows the Lean management philosophy and its effects at a general level.

Assessment criteria, good (3-4)

Knows well the Lean management philosophy and its effects at a general level, applying them in the tasks of the course.

Assessment criteria, excellent (5)

Applies Lean management philosophy and influences commendably in course assignments. Can present his knowledge in assignments related to the themes of the course.

Objective

Theme: Written Communication in Engineering

The student can write various kinds of documents and texts in the field of ICT using appropriate style and terminology and grammatically correct language. The student knows the principle rules of akademic writing. The student knows the purchasing process of a technology company and related documents and terminology.

Proficiency level B2

Content

Purchasing process of a technology company
Business documents
Academic writing
Writing a professional report
Speaking, writing and listening tasks

Location and time

Rovaniemi, spring 2025

Materials

Moodle material

Professional literature

Teaching methods

Contact lessons

Exam schedules

Will be decided at the beginning of the study unit.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student knows the purchasing process of a technology company and the related business documents. The student knows the basics of academic writing and can draw up understandable documents using helping tools.

Assessment criteria, good (3)

The student knows the purchasing process of a technology company and the related business documents and appropriate terminology and phrases. The student knows the principle rules of academic writing and is able to prepare different kinds of documents using appropriate style.

Assessment criteria, excellent (5)

The student knows the purchasing process of a technology company and related documents. The student can draw up related documents using appropriate terminology and phrases and grammatically flawless language. The student knows and understands the rules of academic writing and is able to write grammatically correct academic text.

Assessment methods and criteria

Assessment is based on the European language assessment framework level B2 and the course assignments.

Assessment criteria, fail (0)

The student does not do the course assignments.

Assessment criteria, satisfactory (1-2)

The student knows the basics of academic writing and can draw up understandable documents using helping tools.

Assessment criteria, good (3-4)

The student knows the rules of academic writing and is able to prepare different kinds of documents using appropriate style.

Assessment criteria, excellent (5)

The student can draw up documents using appropriate terminology and phrases and grammatically flawless language. The student knows and understands the rules of academic writing and is able to write grammatically correct academic text.

Objective

The student is able to carry out a development project that includes practical machine learning. The student is able to apply appropriate modern tools and methods to development work. The student is able to make decisions in unforeseen situations and utilize various communication channels and tools in the external and internal communication of the project. The student is capable of multicultural collaboration.

Content

- A multicultural work community
- Automation Testing / DevOps

Location and time

Classes and workshops take place on the Rovaniemi Jokiväylä campus in the scheduled classroom. Additional team meetings will be arranged as needed.

Materials

Selected research articles and online resources provided throughout the course.

Reading:

Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto. Second Edition, MIT Press, Cambridge, MA, 2018

Link: http://incompleteideas.net/book/the-book-2nd.html

Deep Learning (Adaptive Computation and Machine Learning series), An MIT Press book, Ian Goodfellow and Yoshua Bengio and Aaron Courville

Link: https://www.deeplearningbook.org/

Teaching methods

The study module employs project-based learning, where students collaborate in teams to develop practical machine learning and AI solutions utilizing DevOps principles and methods. Regular workshops, seminars, and mentoring sessions will support the project work. Active participation and engagement in all activities are expected.

Employer connections

The study module aims to include collaboration with industry partners, offering students real-world problems to solve. This provides practical experience and networking opportunities within the field.

Exam schedules

There are no traditional exams. Assessment is continuous and based on project milestones, presentations, and final deliverables. Opportunities for resubmission will be provided for components that do not meet the required standards.

International connections

International students are welcome, and all course activities are conducted in English.

Completion alternatives

Alternative completion methods may be applicable through the process of identification and recognition of acquired competencies.

Content scheduling

1. Introduction, team formation, project topic selection
2. Project planning, literature review, initial development
3. Automation and testing
4. Mid-project reviews, implementation
5. Refinement, troubleshooting, preparation for final presentation
6. Final presentations, submission of project reports

Further information

Students are expected to maintain regular communication with instructors and team members. All resources and announcements will be available on the study module's online platform (Moodle).

Evaluation scale

H-5

Assessment methods and criteria

Project Development (50%): Quality, innovation, and functionality of the final product.
Team Collaboration (20%): Contribution to team efforts and effective communication.
Presentations (15%): Clarity, professionalism, and ability to articulate project details.
Documentation (15%): Completeness, clarity, and organization of reports and code documentation.

Final Seminar, Project Reporting and Peer Reviews are essential parts of the assessment.

Grading of 0 to 5 is used where 0 is Fail and 5 is Excellent

Assessment criteria, satisfactory (1-2)

Basic machine learning and AI concepts are implemented, resulting in a product with some functionality. Contribution to team efforts is observable but may be inconsistent. Presentations cover essential aspects of the project but may lack clarity or depth. Documentation provides a basic overview but might be lacking in detail or organization.

Assessment criteria, good (3-4)

Machine learning and AI concepts are applied effectively, producing a functional product with moderate technical complexity. Active participation in team activities is demonstrated, contributing positively to the team's objectives. Presentations are clear and professional, conveying technical details adequately. Documentation is well-organized and offers a good understanding of the project's technical aspects.

Assessment criteria, excellent (5)

Advanced machine learning and AI techniques are applied proficiently, resulting in a highly functional and innovative product. Significant contributions to the team are made, potentially taking on coordination roles and promoting effective collaboration. Presentations are professional and clear, thoroughly explaining the project's technical components. Documentation is comprehensive and well-structured, providing detailed insights into the project's development and implementation.

Objective

The student learns fundamental mathematical concepts, principles, tools (including computing environments) and terminology of statistics, probability and optimization for professional studies.

Content

Theory of statistics and probability
- Numerical and graphical description of data
- Probability, probability rules and theorems, probability distribution
- Modeling, parameter estimation
- Model selection, decision theory
- Analysis task types

Optimization, differential calculus and numerical computation
- Objective function
- Critical points, extrema
- Types of optimization problems
- Limit, derivative, partial derivative, differentiation rules
- Iterative gradient-based optimization methods, derivative-free methods

Location and time

Spring term 2025, 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)

Assessment criteria - grade 1
The student knows the concepts of probability, statistics, and optimization and is able to solve basic problems.

Assessment criteria, good (3)

Assessment criteria - grade 3
The student understands the concepts of probability, statistics, and optimization and is able to solve varied problems related to applications of probability, statistics, and optimization.

Assessment criteria, excellent (5)

The student understands the concepts of probability, statistics, and optimization and is able to apply methods of probability, statistics, and optimization in solving and handling new types of problems.

Assessment methods and criteria

Evaluation is based on exercises (homework) and/or exams. 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 knows the basic concepts of probability, statistics, and optimization, and is able to solve basic problems.

Assessment criteria, good (3-4)

Student understands more complicated concepts of probability, statistics, and optimization, 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 probability, statistics, and optimization to new problems and solve them in exact mathematical language.

Objective

Theme: communication in working life

The student is able to communicate interactively in different working life situations in the field of ICT. The student can prepare and give a professional presentation, make phone calls and use e-mail in an appropriate and professional manner. The student can participate meetings and negotiations and write related documents. The student can tell about their education and discuss topics in the field of ICT. The student can use appropriate style in different situations and consider cultural differences in communication.

Proficiency level B2

Content

Telephone and e-mail communication
Professional presentation and presentation skills
Work of an ICT engineer
Applying for a job, CV, job interview
Meeting terminology
Professional language, terminology and texts
Speaking, writing and listening tasks

Location and time

Autumn 2024, Rovaniemi

Materials

Study material available on Moodle.

Teaching methods

Contact lessons, independent studying

Exam schedules

Exam dates will be decided during the course.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student communicates understandably in English in different working life situations both in writing and speech. The student is able to apply for work using English and knows the language of formal meetings, as well as ICT related terminology.

Assessment criteria, good (3)

The student is able to communicate fairly fluently in English both in speech and in writing and is able to use appropriate style in different situations. The student knows rather advanced terminology of working life and information and communication technology. The student is able to represent their employer in various situations.

Assessment criteria, excellent (5)

The student communicates fluently both in speech and in writing in English using appropriate style. The student uses language structures flawlessly and pronounces fluently and clearly. The student can use correct terminology in various working life situations and masters the terminology of information and communication technology. The student is able to take into account multicultural aspects in communication.

Assessment methods and criteria

Assessment is based on the student's active participation in contact lessons. The required assignments must be done and there is also a written exam. Oral skills will be assessed continuously during the study unit.
The assessment is based on the Common European framework, skill level B2.

Assessment criteria, fail (0)

Student does not fulfill the requirements.

Assessment criteria, satisfactory (1-2)

The student can represent his or her company and present products and work in projects if given enough time and tools to prepare beforehand. The student can use the basic terminology of ICT, uses the basic structures of English mainly correctly and pronounces English understandably.

Assessment criteria, good (3-4)

The student is able to represent own company and products fluently in English using appropriate style. The student uses versatile language structures and vocabulary and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication

Assessment criteria, excellent (5)

The student can represent own company and present products very fluently and accurately using appropriate style. The student uses language structures flawlessly and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication.

Objective

Theme: communication skills in ICT business

The student is able to manage in demanding working life situations in English taking cultural differences into consideration and using appropriate style. The student is able to follow development in ICT domain. The student can represent their employer or company at trade fairs and other occasions and present state-of-the-art ICT technology in English.

Proficiency level B2

Content

Professional language in ICT
ICT companies, types of companies
Representing a company and its products
Negotiations
Trade fairs
ICT projects
Speaking, writing and listening tasks

Location and time

Autumn 2024

Materials

Material available on Moodle

Teaching methods

Contact lessons, independent studying

Exam schedules

The schedule for exams will be decided during the study unit.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student communicates understandably in English about the topics of working life and information and communication technology. The student knows the basic terminology and types of businesses. The student can represent their employer provided that there is a chance to prepare beforehand.

Assessment criteria, good (3)

The student is able to communicate fairly fluently in English both in speech and in writing. The student knows rather advanced terminology of working life and information and communication technology. The student is able to represent their employer in various situations.

Assessment criteria, excellent (5)

The student communicates fluently both in speech and in writing in English. The student uses the terminology of various working life situations and information and communication technology skillfully and is able to take into account multicultural aspects in communication.

Assessment methods and criteria

Assessment is based on student's activity and written and oral exams.

Assessment criteria, fail (0)

Student doesn't fulfill the requirements.

Assessment criteria, satisfactory (1-2)

The student can represent his or her company and present products and work in projects if given enough time and tools to prepare beforehand. The student can use the basic terminology of ICT, uses the basic structures of English mainly correctly and pronounces English understandably.

Assessment criteria, good (3-4)

The student is able to represent their own company and products fluently in English using appropriate style. The student uses versatile language structures and vocabulary and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication.

Assessment criteria, excellent (5)

The student can represent their own company and present products very fluently and accurately using appropriate style. The student uses language structures flawlessly and pronounces fluently and clearly. The student can use appropriate styles in multicultural environments without the language skills restraining communication.

Objective

This course orientates students to electronics lab work. The course introduces students to electronic components, test setups, the basics of device construction and the use of measuring equipment as part of electronics analysis and design. The course is intended for computer science students whose studies do not actually aim at electronics design. The course also introduces microcontrollers (Micro Controller Unit, MCU) and their use in sensor data acquisition and actuator control.

Content

1. Intro to the Course
2. Electrical Safety
3. Basics of Electric Circuits
4. Components in Electronics
5. Signals in Electronics
6. Soldering in Electronics
7. Soldering exercises
8. Measurements in Practice
9. Electronics measurements in practice exercise
10. Computer Aided Engineering (CAE) in electronics
11. Microcontrollers & Sensors in IoT

Location and time

The introductory lectures of the course will be held on week 36. The course includes (4 x 8 + 4) hours of lessons per week, in addition to self-study. There will be no lessons held during the weeks 37, 41. and 42. and the course ends on week 50. The teacher will grade the course by December the 31st at the latest. The Lectures and labs will be held from week 36 to week 43.

Materials

All study material needed for the study course is offered in the study course's workspace.

Teaching methods

The course consists of classroom lessons and laboratory work. The course involves independent work and reporting.

Exam schedules

The course is completed with exercises and reports that are scored. The course does not include an exam, except in specially agreed special cases.

Completion alternatives

For justified reasons, the course can be completed with a closed exam, the content of which is agreed with the individual lecturer.

Content scheduling

A list of topics and techniques covered during the Course:

Labs on-site (from week 37 to week 43)

1. wk. 37. 4th Sept. 2023 08:15 - 16:00
- Intro to the Course.
- Components in Electronics
- Soldering in Electronics. (week assignment #1, 10 pts max.)

2. wk. 38. 20th Sept. 2023 08:15 - 16:00
- Electrical Safety (week assignment #2, 10 pts max.)

3. wk. 39. 29th Sept. 2023 08:15 - 16:00
- Basics Measurements in Electronics (week assignment #3, 10 pts max.)

4. wk. 40. 3rd Oct. 2023 08:15 - 16:00
- Computer Aided Engineering (CAE) in Electronics (week assignment #4, 10 pts max.)

5. wk. 43. (week assignment #5, 10 pts max.)
- AC and distortion analysis exercise. (week assignment #5, 10 pts max.)

Project work (from week 43 to week 49)

Project work report about electronics in Your project (Project report, 10 pts max)

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is able to analyze the basic currents, voltages and powers of an electronic circuit. The student masters the properties of electronic components such as passive components and semiconductors. The student recognizes electronic components such as diodes and transistors as well as integrated circuits such as operational amplifiers and is able to analyze their basic connections.

Assessment criteria, good (3)

In addition to basic analyzes such as current voltages and powers, the student is able to perform frequency level analyzes. The student masters the basics of the analysis of dynamic properties such as delays and responses.

Assessment criteria, excellent (5)

The student is able to choose the connection of analog electronics and analyze its suitability for the current design problem. The student’s design and analysis skills are sufficient to apply the connections.

Assessment methods and criteria

The assessment is based on week assignments and lab reports.

Week assignments are scored 0 to 10 pts.

Participation in laboratory work is assessed with a grade of:
0 pts - did not participate
1 pts - participated
2 pts - returned the weekly asssignment report

The returned reports of the lab reports are evaluated from 0 to 10 pts.

Evaluation scale Note! Rating scale reduced slightly due the fact there is only 5 assignments which weight is big to compared to assignments, also pts. limits was decreased 1pt:

0 - 15 Failed
16 - 21 Grade 1
22 - 28 Grade 2
29 - 34 Grade 3
35 - 41 Grade 4
42 - 50 Grade 5

Assessment criteria, satisfactory (1-2)

The student is able to analyze the basic currents, voltages and powers of an electronic circuit. The student masters the properties of electronic components such as passive components and semiconductors. The student recognizes electronic components such as diodes and transistors as well as integrated circuits such as operational amplifiers and is able to analyze their basic connections.

Assessment criteria, good (3-4)

In addition to basic analyzes such as current voltages and powers, the student is able to perform frequency level analyzes. The student masters the basics of the analysis of dynamic properties such as delays and responses.

Assessment criteria, excellent (5)

The student is able to choose the connection of analog electronics and analyze its suitability for the current design problem. The student’s design and analysis skills are sufficient to apply the connections.

Objective

The student knows and can apply the primary data structures and algorithms. The student can compare their efficiency and complexity.

Content

- Algorithmic complexity and evaluation of the performance of algorithms: the Big O notation.
- The primary data structures and their implementations: arrays, linked lists, stacks, queues, graphs, binary trees.
- The primary algorithms and their implementations: recursion, searching and sorting.

Location and time

Computer labs at Rantavitikka Campus in the autumn term 2024.

Materials

Lecture materials, examples, exercises and assignments in Moodle workspace and/or OneDrive.



Course book

Carrano F. & Henry T. 2018. Data Structures and Abstractions with Java. 5th Edition. Pearson

Recommended reading

Goodrich M. T. & al. 2014. Data Structures and Algorithms in Java: International Student Version. 6th Edition.

Wiley Weiss M. 2012. Data Structures and Algorithm Analysis in Java: International Edition. 3rd Edition. Pearson Education

Teaching methods

Lectures and exercises, assignment and self-supervised work.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student can compare the complexity of algorithms and apply some basic data structures and algorithms.

Assessment criteria, good (3)

The student can compare the complexity of algorithms and apply a variety of data structures and algorithms. The student is familiar with the internal implementation of the most common data structures and algorithms.

Assessment criteria, excellent (5)

The student can evaluate the complexity of algorithms and apply a wide variety of data structures and algorithms. The students is familiar with the internal implementation of the primary data structures and algorithms. The student can choose the most effective data structures and algorithms for a given task.

Objective

The student learns different concepts of entrepreneurship, its importance for economies, and the people involved.

The student learns business idea development that is explored from a theoretical viewpoint as well as from a practical viewpoint.

The student learns to identify, develop, and assess future-oriented business opportunities and ideas.

The student is familiar with business startup theories and processes.

The student can prepare a business plan with its calculations and present the businesses successfully.

The student understands sustainable development, social responsibility and circular economy as part of business and learns about their impact on business models.

Content

- Tools and techniques related to developing a business idea.
- Analyzing a business case and critically assess the quality of entrepreneurial strategies and tactics based on theoretical and practical insights.
- Key theoretical approaches associated with business idea development.
- Launching a start-up company
- Sustainable development, social responsibility and circular economy as part of business and their impact on business models

Location and time

Autumn-24. Jokiväylä campus Rovaniemi.
Implementation period 2.9 - 13.10.2024

Materials

The material shared by the teacher in the Moodle workspace

Teaching methods

Lectures and group work.

Exam schedules

No exam during the course

Content scheduling

Themes in the course
- Entrepreneurship
- Businessplan
- Marketing and customer service
- Finance and financial management

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student understands different concepts of entrepreneurship and its importance for economies.

The student can prepare a business plan.

Assessment criteria, good (3)

The student can utilize business start-up theories and processes.

Assessment criteria, excellent (5)

The student can utilize future-oriented business opportunities and ideas to develop a business plan. The student is familiar with business start-up theories and processes.

Assessment methods and criteria

Successful completion of assigned tasks is required for all tasks.

Objective

The student learns to understand business operations (B2B), supply and distribution networks, customer value, and profitability. The student learns about the current and the future management and leadership. The student learns Lean Management principles in a business or an organization with continuous improvement with small and incremental changes to improve the value of products or services (with improved quality) and decrease wastes, defects, and costs. The student understands the impact of sustainable development and circular economy on industrial engineering.

Content

- How to run business operations.
- Lean management principles; factors contributing to organizational waste; examining ways to eliminate waste; developing & implementing improved organizational processes, for significant impact to the company’s bottom line.
- How lean management today represents a profound change in the competitive business culture and a leading indicator of excellence in the organization
- Basic principles of lean management strategy, in POM (production and operations management) & supply chain management
- How by implementing lean management organizations can improve product & processes without adding any more money, people, equipment, inventory, or space and aim for perfection.

Location and time

Autumn-24. Jokiväylä campus Rovaniemi.
Implementation period 2.9 - 13.10.2024.

Materials

The material shared by the teacher in the Moodle workspace.

Teaching methods

Lectures and group work.

Exam schedules

No exam during the course.

Content scheduling

In the course, we examine the effects of the Lean management method in relation to the following issues.
- Production management
- Quality management
- Logistics
- Lean management

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student knows principles of business operations and Lean management.

Assessment criteria, good (3)

The student can utilize the information of current business operations to improve quality and decrease waste, defects and costs.The student knows the Lean Management principles.

Assessment criteria, excellent (5)

The student understands business operations and can show how by implementing lean management organizations can improve product & processes without adding any more money, people, equipment, inventory or space and aim for perfection.

Assessment methods and criteria

Successful completion of assigned tasks is required for all tasks.

Assessment criteria, satisfactory (1-2)

Knows the Lean management philosophy and its effects at a general level.

Assessment criteria, good (3-4)

Knows well the Lean management philosophy and its effects at a general level, applying them in the tasks of the course.

Assessment criteria, excellent (5)

Applies Lean management philosophy and influences commendably in course assignments. Can present his knowledge in assignments related to the themes of the course.

Objective

The student learns fundamental mathematical concepts, principles, tools and terminology to be applied in professional studies.

Content

- Basics of logic and set theory
- Expressions, equations, inequality
- Functions
- Geometry; 2D, 3D
- Trigonometry

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 algebra, geometry and trigonometry, and is able to solve basic problems.

Assessment criteria, good (3)

The student understands the concepts of algebra, geometry and trigonometry, and is able to solve varied problems related to applications of algebra, geometry and trigonometry.

Assessment criteria, excellent (5)

The student understands the concepts of algebra, geometry and trigonometry, and is able to apply methods of algebra, geometry and trigonometry in solving and handling new types of problems.

Assessment methods and criteria

Evaluation is based on exercises and tests and/or exams . The emphasise 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 subject matter, such as basic calculus of fractions, powers, roots and polynomials. Student is capable of solving basic exercises such as linear equations and quadratic equations, and can solve a missing side and angle of a right triangle using trigonometry and Pythagorean Theorem.

Assessment criteria, good (3-4)

Student understands more complicated concepts of subject matter, such as the properties of quadratic functions and solid geometry. Student is capable of solving versatile exercises such as factoring, inequalities and versatile geometrical problems. Student uses correct mathematical language and can create logical solutions.

Assessment criteria, excellent (5)

Student is capable of applying concepts of subject matter to new problems and solve them in exact mathematical language.

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.