Status message

The course description for the semester you wanted is not published yet. Showing you instead the latest version available.

UC3FDM05 Further Discrete Mathematics

UC3FDM05 Further Discrete Mathematics

  • 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 - Oslo, Online
    • Course Leader
      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’ skills in discrete mathematics in order to advance the practical and theoretical understanding of discrete mathematics. In particular, this course explores Automata, Regular Expressions, Grammars and Turing Machines.

Course Learning Outcomes
Knowledge

The student has knowledge of

K1 definitions of Automata and Turing Machines.
K2 understand and explain the use of Automata, Turing Machines, Regular Expressions and Context-Free Grammars within the field of computing.
Skills

The student gain skills in

S1 ability to design and examine various types of automata.
S2 generate and evaluate regular expressions and context-free grammars.
S3 mathematically analyse computational complexity.
General Competence

The student can demonstrate

G1 the relevance of discrete mathematics to the students’ program of study.
G2 clearly and appropriately present solutions to a variety of automata problems and challenges.
Course Topics
  • Finite State Automata
  • Regular Expressions
  • Context Free Grammars (CFGs)
  • Turing Machines
  • Computational Complexity
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 Hour(s)
Teacher-supported work
24 Hour(s)
Self-study
78 Hour(s)
Work Requirements

 There are no mandatory assignments in this course.

Assessment Strategy

This course has three (3) exams contributing towards the overall and final grade of the course.

All exams must be assessed as passed to receive the final Course Grade.

Form of assessmentGrading scaleGroupingDuration of assessment
Online Test
A-F
Online Test
A-F
Online Exam
A-F