MA111-7-SP-CO:
Foundational Mathematics for Data Science
2021/22
Mathematics, Statistics and Actuarial Science (School of)
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 17 January 2022
Friday 25 March 2022
15
14 July 2021
Requisites for this module
(none)
(none)
(none)
(none)
(none)
MSC G305JS Applied Data Science,
MSC G30624 Data Science and its Applications,
MSC G306JS Data Science and its Applications
The module develops the foundational mathematical skills needed for students studying data science. It will introduce standard mathematical approaches necessary for data science, such as: widely used functions; basics of differentiation and integration; vectors and matrices; different metrics and when they are used; introduction to sets.
This module will support students from a wide range of educational backgrounds, to give them an understanding of the core mathematical skills needed within the study of Data Science. It will introduce students to important mathematical functions and equip them with the techniques needed to solve problems from calculus, linear algebra and discrete mathematics.
By the end of the module students will:
1. Have a comprehensive understanding of basic mathematical functions and be able to plot them.
2. Understand standard mathematical notation
3. Have a comprehensive understanding of the basic rules of the differential and integral calculus for functions of one variable.
4. Be able to perform simple operations on vectors and matrices
5. Have a comprehensive understanding of the mathematical notion of distance and will be able to calculate simple distance metrics.
6. Be familiar with the notion of a set and have a comprehensive understanding of basic set operations
Foundations: logs, exponentials, trigonometry, polynomials, inequalities, mathematical notation, plots of functions.
Calculus: derivatives, integrals.
Linear Algebra: vectors, matrices, metrics.
Discrete: sets and set operations.
The module consists of 2 hours lectures and 1 hour class each week, with an additional five 1 hour lectures spread through the term. With 3 hours revision lectures in the Summer term.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Assignment 1 |
|
10% |
| Coursework |
Assignment 2 |
|
10% |
| Written Exam |
Final test |
|
80% |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Joseph Bailey, email: jbailef@essex.ac.uk.
Dr Dan Brawn
Dr Dan Brawn (dbrawn@essex.ac.uk)
Yes
Yes
Yes
Dr Yinghui Wei
University of Plymouth
Available via Moodle
Of 1599 hours, 20 (1.3%) hours available to students:
1579 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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