NUS8305 : Mathematical Foundations of Machine Learning
- Offered for Year: 2024/25
- Module Leader(s): Dr Mohammed Abdul Hannan
- Lecturer: Dr Pavan Kumar Naraharisetti
- Owning School: NUIS
- Teaching Location: Singapore
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
This module aims to provide fundamental knowledge and skills in mathematics related to Machine Learning and Data Analytics so that students can either build their Machine Learning tools in the future or use existing tools with confidence since they would know the “science behind” such tools. This is done by teaching linear, non-linear models in addition to ordinary differential equations and statistical models.
Outline Of Syllabus
1. Introduction
a. Mathematical modelling.
b. Simulation – Optimisation.
c. Digital Twin and Machine Learning.
2. First Principles models
a. Linear algebra including eigenvalues and eigenvectors.
b. First and second-order systems.
3. System of systems: series
4. Optimisation and Parameter Estimation
5. Lean Data and Design of Experiments
6. Statistics
a. PCA and Model Reduction.
b. Mathematics of Statistical Process Control
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 1 | 18:00 | 18:00 | Coursework assignment preparation |
| Guided Independent Study | Assessment preparation and completion | 1 | 1:00 | 1:00 | Quiz |
| Scheduled Learning And Teaching Activities | Lecture | 12 | 2:30 | 30:00 | Lectures |
| Guided Independent Study | Assessment preparation and completion | 1 | 17:00 | 17:00 | Preparation for quiz |
| Guided Independent Study | Assessment preparation and completion | 1 | 2:00 | 2:00 | Final exam |
| Guided Independent Study | Assessment preparation and completion | 1 | 24:00 | 24:00 | Revision for exam |
| Scheduled Learning And Teaching Activities | Small group teaching | 12 | 1:00 | 12:00 | Tutorials |
| Guided Independent Study | Independent study | 12 | 2:00 | 24:00 | Lecture follow-up |
| Guided Independent Study | Independent study | 1 | 60:00 | 60:00 | Review lecture notes, general reading, background reading, reading specified articles |
| Guided Independent Study | Independent study | 1 | 12:00 | 12:00 | Tutorial preparation |
| Total | 200:00 |
Teaching Rationale And Relationship
Teaching is conducted via lectures and tutorial with small group discussions during class. This is complemented with self-study and preparation of tutorial solutions, coursework/project and final examination in order to provide feedback on student learning. Teaching materials are made available to the students online in order for self-study and preparation at their own pace. Tutorial classes enable students to ask questions and clarify any doubts.
Due to the emerging Covid-19 situation, it is likely that some or all of the classes are conducted online. Attendance will be taken irrespective of whether the class is online or face-to-face, and students are expected to switch on their camera for online classes.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Written Examination | 120 | 2 | A | 80 | Final exam |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Written exercise | 2 | M | 20 | Assignment on multiple problems that give an opportunity to apply concepts taught in class. Team report 1500 words per student max |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Prob solv exercises | 2 | M | 60 mins quiz |
Assessment Rationale And Relationship
Coursework assignment provides students more time to think about a larger problem and provide solutions to it. It also allows them to work as a team to handle more significant problems. The quiz allows the students to test the knowledge gained thus far and better plan the rest of the study. The written exam enables students to demonstrate understanding and apply knowledge and skills learnt to solve engineering problems using known mathematical methods
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- NUS8305's Timetable