Algorithmic Foundations 2 COMPSCI2003

  • Academic Session: 2024-25
  • School: School of Computing Science
  • Credits: 10
  • Level: Level 2 (SCQF level 8)
  • Typically Offered: Semester 1
  • Available to Visiting Students: Yes
  • Collaborative Online International Learning: No

Short Description

To introduce the foundational mathematics needed for Computing Science; To make students proficient in their use; To show how they can be applied to advantage in understanding computational phenomena.

Timetable

Two 1-hour lectures per week; nine one-hour Tutorials held over the course of the semester.

Requirements of Entry

Entry to Level 2 Computing Science is guaranteed to students who achieve a GPA of B3 or better in their level 1 courses at the first sitting. All others would be at the discretion of the School.

 

All grades for Computing Science courses must be at D3 or better at either attempt.

Excluded Courses

None

Co-requisites

None

Assessment

1.5 hour examination (80%); plus assessed coursework (20%) and in-class quizzes 5%

Main Assessment In: December

Are reassessment opportunities available for all summative assessments? No

Reassessments are normally available for all courses, except those which contribute to the Honours classification. For non Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

 

The coursework cannot be redone because the feedback provided to the students after the original coursework would give any student redoing the coursework an unfair advantage.

Course Aims

To introduce the foundational mathematics needed for Computing Science; To make students proficient in their use; To show how they can be applied to advantage in understanding computational phenomena.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. translate simple English sentences into the notation of predicate logic, set theory and relational algebra;

2. use predicate logic, set theory, and relational algebra to write assertions;

3. use laws to prove assertions in predicate logic, set theory, and relational algebra;

4. demonstrate an understanding of inductively-generated structures and proofs by induction;

5. deploy the basic concepts of combinatorics;

6. understand the basic principles of discrete probability theory and apply them to simple problems.

Minimum Requirement for Award of Credits

Submission of at least one of the 2 assessed exercises.