MEK2000 Mathematics 2000 Course description

This course, together with Mathematics 1000, will give the students an understanding of mathematical concepts, problems and solution methods with the focus on application, particularly in engineering subjects.

Two internal examiners will assess the report and oral examination. External examiner is used periodically.

The course focuses on the technical aspects of the implementation of user interfaces.

No formal requirements over and above the admission requirements.

A student who has completed this course should have the following learning outcomes, defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of this course the student

• has specialized knowledge of frameworks and APIs for developing user interfaces
• has specialized knowledge of real-time programming
• has advanced knowledge of copyright, ownership and intellectual property with reuse of code

Skills

On successful completion of this course the student

• will be acquainted with new frameworks, platforms and APIs for developing user interfaces
• can use current development environments
• can analyse the suitability of design patterns for problem-solving in universal design and user interfaces
• can use agile development methods

General competence

On successful completion of this course the student

• can analyse development processes and make decisions that maximize reuse and minimize costs
• can apply knowledge of APIs, frameworks and developing skills in new areas and carry out advanced assignments and projects

This course is organized as a series of lectures which cover the central parts of the theory.

Guest lectures can be organised on chosen topics. Students work in groups on projects under supervision.

Individual written exam under supervision, 3 hours.

The exam result can be appealed.

All printed and written aids.

Calculator.

The course covers topics selected for their particular relevance to the students' intended doctoral thesis. The material for the course is composed in collaboration with the thesis supervisor, and the course proceeds as a self-study under expert supervision. The course is completed by student giving a seminar on a particular topic within the scope of the course material.

Recommended previous experience: Master’s degree in robotics and control, or related field. Basic mathematical knowledge in calculus, mechanics, linear algebra, statistics, probability theory, and programming.

The course will be offered once a year, provided 3 or more students sign up for the course. If less than 3 students sign up for a course, the course will be cancelled for that year.

For the final assessment a grading scale from A to E is used, where A denotes the highest and E the lowest pass grade, and F denotes a fail.

Students who complete the course are expected to have the following learning outcomes, defined as knowledge, skills and general competence:

Knowledge

On successful completion of the course, the student:

• has in-depth knowledge within specific topics in robotics and control that supplement the specialisation syllabus.
• is at the forefront of knowledge within the topic of his/her doctoral thesis project.
• has a profound understanding of the state-of-the-art and the latest developments in the field relevant to his/her doctoral thesis.

Skills

On successful completion of the course, the student can:

• apply theoretical knowledge, scientific methods and simulation tools suitable for solving complex robotics and control problems.
• plan and conduct scholarly work within the topic of his/her the doctoral thesis project.
• analyse existing theories, methods and standardised solutions on practical and theoretical engineering problems.

General competence

On successful completion of the course, the student:

• is competent in literature study, self-study and research-based learning
• can apply his/her knowledge and skills to carrying out advanced tasks and projects.
• can communicate issues, analyses and solutions to both specialists and non-specialists.
• can assess the need for, and initiate innovation in his/her field of expertise.