| Unit name | Applied Analysis B |
|---|---|
| Unit code | MATH10024 |
| Credit points | 20 |
| Level of study | C/4 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Sadowski |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
none |
| Units you must take alongside this one (co-requisite units) |
none |
| Units you may not take alongside this one |
none |
| School/department | School of Mathematics |
| Faculty | Faculty of Science |
Why is this unit important?
Applied Analysis B provides a rigorous exposition of differentiation, integration and optimisation in R^n. It also shows how these concepts and methods can be applied in the context of typical Data Science problems (e.g. dimension reduction and support vector machines). It equips the students with a number of basic mathematical tools indispensable to every Data Scientists.
How does this unit fit into your programme of study
Applied Analysis B generalises concepts and methods presented in Applied Analysis A to dimension n. It also uses techniques and ideas developed in other first year units such as Matrix Algebra and Algorithms and Programming to familiarise the students with various optimisation methods. It provides the bedrock of knowledge necessary to study more advanced Data Science units.
An overview of content
Applied Analysis B focuses on differentiation of multivariable functions. It presents basic methods of Multivariable Calculus and introduces gradients, Hessian matrices, Lagrangian multipliers and integrals in dimension n. It studies optimisation problems with and without constraints and explains how multivariable calculus can be applied to solve a number of problems in Data Science.
Learning Outcomes
At the end of the unit, the students should be able to:
The unit will be taught through a combination of
Assessment for learning/Formative assessment:
Assessment of learning/Summative assessment:
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. MATH10024).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
