Mathematics for Information Studies

Course manual 2024/2025

Course content

This course is designed to provide students with the mathematical background that is necessary to follow other courses in the bachelor Informatiekunde, such as Network Science, Recommender Systems, Applied Machine Learning, etc. The goal is to make students feel comfortable working with basic concepts from calculus, probability theory and linear algebra. Moreover, we will introduce those concepts using applications from machine learning, data sciences, etc., so that students are already exposed to the use of mathematics in those areas.

Objectives

• can compute basic derivatives and is able to use them to solve simple applied problems
• apply basic combinatorics in simple scenarios
• understand and use the main results in basic probability theory, such as correlation and independent variables and Bayes' rule
• can perform calculations with discrete and continuous probabilities
• can perform basic vector and matrix operations and is able to use them to modelize and solve simple applied problems

Teaching methods

• Lecture
• Seminar

Learning activities

Attendance

Programme's requirements concerning attendance (OER-B):

• For practical trainings and tutorials, with assignments, attendance is obligatory, unless stated differently in the course catalogue. When students do not meet the requirements for attendance, he or she cannot finish the course with a pass mark. The requirements concerning attendance for lectures/seminars, if applicable, are stated in the course catalogue.
  

Additional requirements for this course:

The attendance to the werkcollege is mandatory, but students may miss up to 3 werkcollege due to sickness, personal reasons, etc.

Assessment

The final grade is determined in the following way:

Practical exercises (consisting of homework and laptop assignments) counts for 30% of the final grade. Theoretical material, tested with two partial exams counts for 70% (of which 35% is for the first partial exam and 35% for the second partial exam).

To pass the course, the final grade must be at least a 5.5, and the component grades for both the theoretical material and the practical exercises must be at least a 5.5.

The resit exam concerns the theoretical material. The resit exam is only accessible to students who have sufficiently completed the assignments (with at least a 5.5).

Assignments

The homework and laptop assignments are individual and are graded in canvas.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Contact information

Coordinator

• Gaelle Fontaine