MA20278: Machine learning 1
[Page last updated: 03 August 2022]
Academic Year:  2022/23 
Owning Department/School:  Department of Mathematical Sciences 
Credits:  6 [equivalent to 12 CATS credits] 
Notional Study Hours:  120 
Level:  Intermediate (FHEQ level 5) 
Period: 
 Semester 2

Assessment Summary:  EX75CW25 
Assessment Detail: 
 Assessment detail for this unit will be available shortly.

Supplementary Assessment: 
 Likeforlike reassessment (where allowed by programme regulations)

Requisites: 
Before taking this module you must take MA20222

Learning Outcomes:
 After taking this unit students shuold be able to:
* Identify and formulate ML problems from practical situations and judge the suitability of different ML approaches.
* Write code to implement basic ML algorithms in Python.
* Understand the mathematics underlying these techniques.

Aims:  This course will introduce students to a range of Machine Learning (ML) techniques and algorithms for supervised and unsupervised learning.

Skills:  Formulation of ML problems TF, model selection TF, writing code in python TFA, linear algebra TA, optimization TA.

Content:  Machine Learning algorithms and supporting techniques and mathematics including some of the following:
Classification algorithms: K nearest neighbours, naive Bayes, logistic regression, decision trees.
Regression algorithms: K nearest neighbours, linear regression, decision trees.
Unsupervised learning: linear dimensionality reduction, Kmeans.
Machine learning techniques/concepts: data splitting, cross validation, formulation of ML problems, overfitting, model selection.
Underlying mathematics: optimization concepts, lowrank matrix approximation, Bayes rule.

Programme availability: 
MA20278 is Compulsory on the following programmes:
Department of Mathematical Sciences
 USMAAFB20 : BSc(Hons) Mathematics, Statistics, and Data Science (Year 2)
 USMAAAB20 : BSc(Hons) Mathematics, Statistics, and Data Science with Study year abroad (Year 2)
 USMAAKB20 : BSc(Hons) Mathematics, Statistics, and Data Science with Industrial Placement (Year 2)
MA20278 is Optional on the following programmes:
Department of Mathematical Sciences
 USMAAFB15 : BSc(Hons) Mathematical Sciences (Year 2)
 USMAAFB15 : BSc(Hons) Mathematical Sciences (Year 3)
 USMAAAB16 : BSc(Hons) Mathematical Sciences with Study year abroad (Year 2)
 USMAAAB16 : BSc(Hons) Mathematical Sciences with Study year abroad (Year 4)
 USMAAKB16 : BSc(Hons) Mathematical Sciences with Year long work placement (Year 2)
 USMAAKB16 : BSc(Hons) Mathematical Sciences with Year long work placement (Year 4)
 USMAAFB13 : BSc(Hons) Mathematics (Year 2)
 USMAAFB13 : BSc(Hons) Mathematics (Year 3)
 USMAAAB14 : BSc(Hons) Mathematics with Study year abroad (Year 2)
 USMAAAB14 : BSc(Hons) Mathematics with Study year abroad (Year 4)
 USMAAKB14 : BSc(Hons) Mathematics with Year long work placement (Year 2)
 USMAAKB14 : BSc(Hons) Mathematics with Year long work placement (Year 4)
 USMAAFB01 : BSc(Hons) Mathematics and Statistics (Year 2)
 USMAAFB01 : BSc(Hons) Mathematics and Statistics (Year 3)
 USMAAAB02 : BSc(Hons) Mathematics and Statistics with Study year abroad (Year 2)
 USMAAAB02 : BSc(Hons) Mathematics and Statistics with Study year abroad (Year 4)
 USMAAKB02 : BSc(Hons) Mathematics and Statistics with Year long work placement (Year 2)
 USMAAKB02 : BSc(Hons) Mathematics and Statistics with Year long work placement (Year 4)
 USMAAFB05 : BSc(Hons) Statistics (Year 3)
 USMAAAB06 : BSc(Hons) Statistics with Study year abroad (Year 4)
 USMAAKB06 : BSc(Hons) Statistics with Year long work placement (Year 4)
 USMAAFM14 : MMath(Hons) Mathematics (Year 2)
 USMAAFM14 : MMath(Hons) Mathematics (Year 3)
 USMAAAM15 : MMath(Hons) Mathematics with Study year abroad (Year 2)
 USMAAKM15 : MMath(Hons) Mathematics with Year long work placement (Year 2)
 USMAAKM15 : MMath(Hons) Mathematics with Year long work placement (Year 4)

Notes:  This unit catalogue is applicable for the 2022/23 academic year only. Students continuing their studies into 2023/24 and beyond should not assume that this unit will be available in future years in the format displayed here for 2022/23.
 Programmes and units are subject to change in accordance with normal University procedures.
 Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any prerequisite rules.
 Find out more about these and other important University terms and conditions here.
