UC3PMC05 Pure Mathematics for Computing

UC3PMC05 Pure Mathematics for Computing

  • Course description
    • NQF Level
      Bachelor's degree (Level 6 1. Cycle)
    • Area of Study
      Computing
    • Program of Study
      Applied Data Science
    • ECTS
      05
    • Campus
      Kristiansand, OnlinePLUS - Bergen, OnlinePLUS - Oslo, Online
    • Course Leader
      Prof. Seifedine Kadry
Introduction

Language of Instruction and assessment: English
May be offered on Campus and Online.
May be offered as a separate course.
May be offered as an elective course for Computing degrees.

Included in the following bachelor's degrees:

  • Applied Data Science
  • Cyber Security
  • Digital Forensics
Course Aim(s)

This course aims to build upon students’ previous skills in mathematics in order to further develop a practical and theoretical understanding of pure mathematical principles, theories and techniques.

Course Learning Outcomes
Knowledge

The student has knowledge of

K1 the principles and theory of geometry.
K2 the principles and theory of differentiation and integration.
Skills

The student gain skills in

S1 solve a variety of pure mathematics problems through the application of appropriate techniques.
General Competence

The student can demonstrate

G1 the relevance of pure mathematics to the students’ program of study.
G2 clearly and appropriately present solutions to a variety of mathematical problems and challenges.
Course Topics
  • Mathematical Induction
  • Coordinate Geometry
  • Vectors
  • Calculus – Differentiation
  • Calculus - Integration
Teaching Methods
  1. Teaching will be based on a hybrid-flexible approach. Instructor-led face-to-face learning is combined with online learning in a flexible course structure that gives students the option of attending sessions in the classroom, participating online, or doing both.
  2. All activities require active student participation in their own learning.
  3. Learning delivery methods and available resources will be selected to ensure constructive alignment with course content, learning outcomes and assessment criteria.
  4. Students will be taught using a mixture of guidance, self-study, and lecture material. Topics will be introduced in a series of weekly lectures. The guidance sessions will be directed practical exercises and reading in which students can explore topics with support from a teacher. This material will also require students to self-manage their time to ensure tasks are completed and the theory is fully understood. This will allow the students to fully engage with lectures and with their peers.
Resources and Equipment
  1. Learning resources are available in the LMS and include, but is not limited to:
    • literature and online reading material (essential and recommended)
    • streams, recordings and other digital resources, where applicable
    • video conferencing and communication platforms, if applicable
    • tools, software and libraries, where applicable
  2. Students must have access to an internet connection, and suitable hardware.
    • Accessing live streams and virtual laboratories requires a minimum broadband connection of 2Mbps (4Mbps recommended).
  3. Students working on their own laptop/computer are required to acquire appropriate communications software, e.g., webcam, microphone, headphones.
Prerequisite Knowledge

UC1DMA10 Discrete Mathematics, or equivalent course(s).

Reading List

The reading list for this course and any additional electronic resources will be provided in the LMS.

Study Workload

125 nominal hours.
Study workload applies to both Campus and Online students.

ActivityDuration
Teacher-led activity
12
Teacher-supported work
24
Self-study
78
Work Requirements

 There are no mandatory assignments in this course.

Assessment Strategy

This course has one (1) exam contributing towards the overall and final grade of the course.

The exam must be assessed as passed to receive the final Course Grade.

Form of assessmentGrading scaleGroupingDuration of assessment
Online Exam
A-F