CS1MANU: Mathematics and Computation

Module code: CS1MANU

Module provider: Computer Science; School of Mathematical, Physical and Computational Sciences

Credits: 20

Level: 4

When you'll be taught: Semester 1

Module convenor: Professor Richard Mitchell, email: r.j.mitchell@reading.ac.uk

NUIST module lead: Liping Yin, email: lpyin@nuist.edu.cn

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: No

Last updated: 11 December 2024

Overview

Module aims and purpose

The module considers the application of relevant mathematics and associated algorithms as they relate to computer science and data science. Relevant mathematics is revised or introduced, in linear algebra and data analysis, including probability and statistics. These are related to computer science applications and applied through implementations in MATLAB.

Dr Pin Mei will also teach on this module.  

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Perform calculations with matrices and vectors 
2. Draw and interpret graphs 
3. Use probability and statisticsin the context of the subject 
4. Extract useful information from dataand visualise data 

Module content

The module will cover the following topics:

• Linear Algebra
  • Matrix Operations
  • Linear transforms
  • Determinant/Inverse
  • Vectors
  • Gaussian Elimination
  • Eigenvalues/vectors
• Graphical Representation
  • Of relevant functions
  • Interpret graphs
  • Use MatLab
• Complex Numbers
  • Basic complex numbers, such as solving quadratic equations, simple operations
• Calculus
  • Concepts in differentiation and integration relating to simple functions, sinusoids and exponentials
  • Chain rule
  • Finding Maxima and Minima and Newton Raphson
  • Simple partial differentiation
  • Taylor Series and modelling
  • Numerical calculus, including discrete Taylor Series
• Probability and Statistics
  • Simple Probabilities
  • Distribution
  • Data Analysis
  • Correlation
  • Introduction to Data Visualisation

Structure

Teaching and learning methods

This module is delivered through lectures of 4 hours and tutorial of 1 hour as well as PC lab session of 1 hour for ten weeks followed by a week dedicated to consolidation.

Study hours

At least 60 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

The tutorial and lab sessions will be used to practice the concepts. There will be quizzes on Blackboard that can also be used for practice.

Reassessment

Additional costs