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Postgraduate course

Selected Topics in Machine Learning

  • ECTS credits10
  • Teaching semesterSpring, Autumn
  • Course codeINF368
  • Number of semesters1
  • LanguageEnglish or Norwegian
  • Resources

Level of Study

master/ph.d.

Teaching semester

Irregular

Objectives and Content

The course deals with current topics in machine learning, and its content will vary from time to time the course is taught. Topic for spring semester 2020: "Deep learning"

Learning Outcomes

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student

  • knows the main methods in the considered field/topic.

Skills

The student

  • is able to apply the main methods in the considered field/topic in order to solve concrete problems.

Required Previous Knowledge

At least 120 ECTS in computer science, preferably including some mathematics

Recommended Previous Knowledge

INF264/INF283 or equivalent knowledge.

Access to the Course

Access to the course requires admission to a master's programme at The Faculty of Mathematics and Natural Sciences

Teaching and learning methods

Varies. The course may contain lectures, exercises and projects.

Compulsory Assignments and Attendance

Compulsory assignments are valid for one subsequent semesters.

Forms of Assessment

Oral exam. The compulsory exercises can be graded and this grade can count for the final grade. Both the exam and the compulsory exercises must be passed.

Due to the measures taken to avoid the spread of SARS-CoV-2, UiB is closed for teaching and assessment. As a consequence, the following changes is made to assessment spring semester 2020:

  • Written home examination instead of oral examination

Examination Support Material

None

Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Assessment Semester

Examination both spring semester and autumn semester. In semesters without teaching the examination will be arranged at the beginning of the semester.

Reading List

The reading list will be available within June 1st for the autumn semester and December 1st for the spring semester

Course Evaluation

The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department.

Programme Committee

The Programme Committee is responsible for the content, structure and quality of the study programme and courses.

Course Coordinator

Course coordinator and administrative contact person can be found on Mitt UiB, or contact Student adviser

Course Administrator

The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.

Contact

Contact Information

Student adviser:

Student adviser

T: 55 58 42 00

Exam information

  • For written exams, please note that the start time may change from 09:00 to 15:00 or vice versa until 14 days prior to the exam. Autumn 2020 written exams will be arranged either at home or on campus. Please see course information on MittUiB.

  • Type of assessment: Written examination

    Date
    17.09.2020, 09:00
    Duration
    3.5 hours
    Withdrawal deadline
    03.09.2020
    Examination result announcement
    22.09.2020
    Examination system
    Inspera
    Digital exam