Module Specification

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
1. Module Title Analytic Techniques for Computer Science
2. Module Code COMP116
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester Second Semester
7. CATS Level Level 4 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Professor PE Dunne Computer Science P.E.Dunne@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Mrs J Birtall School of Electrical Engineering, Electronics and Computer Science Judith.Birtall@liverpool.ac.uk
13. Board of Studies
14. Mode of Delivery
15. Location Main Liverpool City Campus
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
16. Study Hours 30

  10

      40
17.

Private Study

110
18.

TOTAL HOURS

150
 
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other
19. Timetable (if known)            
 
20. Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

 
21. Modules for which this module is a pre-requisite:

 
22. Co-requisite modules:

 
23. Linked Modules:

 
24. Programme(s) (including Year of Study) to which this module is available on a mandatory basis:

25. Programme(s) (including Year of Study) to which this module is available on a required basis:

26. Programme(s) (including Year of Study) to which this module is available on an optional basis:

27. Aims
 

To equip students with an awareness of the range of methodologies that have been brought to bear in the treatment of computational issues.
To provide practical experience in how various formal approaches can be used to address such issues.

 
28. Learning Outcomes
 

(LO1) Students will have a basic understanding of the range of techniques used to analyse and reason about computational settings.

 

(LO2) Students will have the ability to solve problems involving the outcome of matrix-vector products as might arise in standard transformations.

 

(LO3) Students will have the ability to apply basic rules to differentiate and integrate commonly arising functions.

 

(LO4) Students will have a basic understanding of manipulating complex numbers and translating between different representations.

 

(LO5) Students will have a basic understanding of the role of Linear algebra (including eigenvalues and eigenvectors) in computation problems such as web page ranking.

 

(S1) Problem Solving - Numeracy and computational skills

 

(S2) Problem Solving – Analysing facts and situations and applying creative thinking to develop appropriate solutions.

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lecture
Description: 3 lectures per week throughout semester
Attendance Recorded: Yes

Teaching Method 2 - Tutorial
Description: 1 tutorial/problem class per week throughout semester
Attendance Recorded: Not yet decided

Standard on-campus delivery
Teaching Method 1 - Lecture
Description: Mix of on-campus/on-line synchronous/asynchronous sessions
Teaching Method 2 - Tutorial
Description: On-campus synchronous sessions

 
30. Syllabus
   

Computation as static measurement: Numbers and types of number: integer, rational, irrational. Structured forms: Vectors and vector operations. Linear transformations. Applications in video games and robot motion planning. (3 lectures)

Computation as dynamic measurement: Introduction to calculus; functions and their graphs: geometric interpretation of derivative; standard differentiation formulae and rules; maxima and minima, information obtained from second derivative; basic integral calculus; geometric interpretation of integral; standard integral formulae. (5-6 lectures)

Beyond traditional notions of number : Definition of complex number, representation forms (coordinate, polar), properties of complex numbers: conjugates, modulus, standard arithmetic operations. (3 lectures)
Computational approaches for hard calculations: Providing support for experimental claims: regression methods (1-2 lectures)

Computational models of richer structures: Linear and Matrix algebra; common computational objects described by matrices; weighted directed graphs; properties and operations on matrices: determinant, singularity and invertibility; eigenvalues and eigenvectors; conditions guaranteeing existence of useful forms - the Perron-Frobenius Theorem: notable applications of the PF-eigenvector: Google page ranking algorithm; ranking of sports leagues. (8-9 lectures)
A bit of information theory: Shannon's Fundamental questions: What is information? How is it measured? Shannon's model of communication; information content as reduced uncertainty; the notion of information entropy and the Source Coding Theorem. Dealing with noise and redundancy coding; higher levels: entropy and redundancy in Natural language; very informal introduction to n-gram language models and applications: text prediction, plagiarism/collusion detection (5-7 lectures)

 
31. Recommended Texts
  Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
 

Assessment

32. EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (116) Final Exam There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2 exam schedule 120 60
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (116.3) Class Test 3 There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2 0 15
  (116.1) Class Test 1 There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2, Week 4 0 10
  (116.2) Class Test 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2, Week 8 or 9 0 15