# Computer Science

## ECMM406 - Tools and Techniques **NOT RUNNING IN 2012/3** (2012)

MODULE TITLE CREDIT VALUE Tools and Techniques **NOT RUNNING IN 2012/3** 15 ECMM406 Dr Jovisa Zunic (Coordinator)
DURATION: TERM 1 2 3
DURATION: WEEKS 11 weeks 0 0
DESCRIPTION - summary of the module content

This module provides you with a basic knowledge of programming and of the mathematical tools and techniques necessary to pursue further modules within the area of Applied Artificial Intelligence. This knowledge will enable you to utilise the related literature and understand the theory and methods presented.

AIMS - intentions of the module

The aim of the module is to ensure that you have a sound foundation in programming and mathematical skills to enable you to read scientific research papers and engage in quantitative research in computer science.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

Module Specific Skills and Knowledge:
1  develop knowledge and understanding of the principles and computational approaches for addressing applied computing problems.
2 design, write and test programs written in Matlab
3  apply ideas in linear algebra, calculus and probability
Discipline Specific Skills and Knowledge:
4 understand the theoretical underpinnings and practice of computer science
Personal and Key Transferable/ Employment Skills and  Knowledge:
5 select and use appropriate tools for problems solving
6 Communicate effectively in writing

SYLLABUS PLAN - summary of the structure and academic content of the module

1. Matlab:  Basic programming concepts;  variables,  control structures; procedural programming; I/O; structures, data visualisation.
2. Linear algebra: vectors;  combination of vectors;  scalar and vector products;  linear combinations, span, bases; matrices;  matrix combination; matrix-vector combination;  null space and rank; properties of orthogonal and symmetric matrices; solutions of systems of equations; determinants;  eigenvalues and eigenvectors; singular value decomposition.
3. Calculus: single variable differentiation and integration, and applications; partial differentiation, extrema and saddle points in several dimensions; Jacobians; multivariate integration; numerical methods for integration and differentiation.
4. Probability: sample spaces; probability as frequency and axioms; counting, permutations and combinations; independence and conditional probability; Bayes' rule; discrete distributions;  moments; probability density functions; common density functions.

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
 Scheduled Learning & Teaching Activities Guided Independent Study 25 125
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
 Category Hours of study time Description Scheduled Learning & Teaching activities 20 Lectures Scheduled Learning & Teaching activities 5 Workshops and surgeries Guided independent study 40 Coursework Guided independent study 85 Lecture & assessment preparation; private study

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade

None

SUMMATIVE ASSESSMENT (% of credit)
 Coursework Written Exams 100 0
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Matlab assignment 25 Approx. 8 pages 1,2,4,5 Written
Linear algebra assignment 25 Approx. 8 pages 1,3,4,5,6 Written
Calculus assignment 25 Approx. 8 pages 1,3,4,5,6 Written
Probability assignment 25 Approx. 8 pages 1,3,4,5,6 Written

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-reassessment
All above Coursework (100%) All Completed over the summer with a deadline last week of August

RE-ASSESSMENT NOTES

If a module is normally assessed entirely by coursework, all referred/deferred assessments will normally be by assignment.
If a module is normally assessed by examination or examination plus coursework, referred and deferred assessment will normally be by examination. For referrals, only the examination will count, a mark of 40% being awarded if the examination is passed. For deferrals, candidates will be awarded the higher of the deferred examination mark or the deferred examination mark combined with the original coursework mark.

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

ELE – http://vle.exeter.ac.uk