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Unit information: Mathematics for Computer Science B in 2020/21

Unit name Mathematics for Computer Science B
Unit code COMS10013
Credit points 20
Level of study C/4
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Professor. Calway
Open unit status Not open
Pre-requisites

COMS10014 Mathematics for Computer Science A

Co-requisites

None

School/department Department of Computer Science
Faculty Faculty of Engineering

Description

This unit and its pre-requisite, COMS10014 Mathematics for Computer Science A, provide the mathematical foundations for the rest of the programme.

This unit introduces students to three areas of mathematics:

  • Linear Algebra
  • Analysis
  • Statistics

This unit also continues to expand students’ ability to reason mathematically, e.g. to employ precision and abstraction, and to recognise which mathematical tool is right for which situation.

Intended learning outcomes

Building on COMS10014 Mathematics for Computer Science A, about completing this unit, students will be able to:

  1. Perform the calculations, algorithms and other techniques taught in the unit.
  2. Recognise and apply mathematical precision and abstraction.
  3. Select appropriate mathematical tools and methods of reasoning to create models and solve problems.
  4. Solve problems in the areas of linear algebra, analysis and statistics.

Teaching details

Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, practical activities supported by drop-in sessions, problem sheets and self-directed exercises.

Assessment Details

100% summer timed assessment.

In addition to the assessment, this unit has a "must pass" hurdle: students are required to attend and sign in to at least 75% of the workshop classes.

Reading and References

This unit covers topics that are not found in this particular configuration in any one textbook, so the list below gives examples of books that cover different sections of the unit. Students are highly recommended to not buy any textbooks up front, and certainly not all of the books on the list – rather, they should use them as reference material as and when needed, and only to spend money on a book if it has repeatedly proved useful to them.

  • Strang, Gilbert, Introduction to Linear Algebra (Wellesley-Cambridge Press, 2016) ISBN: 978-0980232776
  • Strang, Gilbert, Linear Algebra and its Applications (Cengage Learning, 2005) ISBN: 978-0030105678
  • James, Glynn, Modern Engineering Mathematics (Pearson Education, 2015) ISBN: 978-1292080734

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