UC3FDM05 Further Discrete Mathematics
UC3FDM05 Further Discrete Mathematics
- Course description
- NQF LevelBachelor's degree (Level 6 1. Cycle)
- Area of StudyComputing
- Program of StudyApplied Data Science
- ECTS05
- CampusKristiansand, OnlinePLUS - Bergen, OnlinePLUS - Oslo, Online
- Course LeaderSeifedine Kadry
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
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.
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. |
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. |
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. |
- Finite State Automata
- Regular Expressions
- Context Free Grammars (CFGs)
- Turing Machines
- Computational Complexity
- 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.
- All activities require active student participation in their own learning.
- Learning delivery methods and available resources will be selected to ensure constructive alignment with course content, learning outcomes and assessment criteria.
- 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.
- 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
- 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).
- Students working on their own laptop/computer are required to acquire appropriate communications software, e.g., webcam, microphone, headphones.
UC1DMA10 Discrete Mathematics, or equivalent course(s).
The reading list for this course and any additional electronic resources will be provided in the LMS.
| Activity | Duration |
|---|---|
Teacher-led activity | 12 Hour(s) |
Teacher-supported work | 24 Hour(s) |
Self-study | 78 Hour(s) |
This course has two (2) 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 assessment | Grading scale | Grouping | Duration of assessment |
|---|---|---|---|
Online Exam | A-F | ||
Term Paper | A-F |