Module Details |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | Maths and Statistics for AI and Data Science | ||
Code | COMP533 | ||
Coordinator |
Professor LA Gasieniec Computer Science L.A.Gasieniec@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2022-23 | Level 7 FHEQ | First Semester | 15 |
Aims |
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This module aims to cover the key concepts and techniques from linear algebra, |
Learning Outcomes |
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(LO1) Good understanding of basic mathematical principles and methods of interest to data scientists. The main focus is on differential calculus and linear algebra. |
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(LO2) Critical awareness of basic and more specialised concepts in probability theory and statistics relevant to data science. |
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(LO3) Ability to undertake a small software project in the domain of data science. |
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(LO4) Ability to communicate the outcome of experimental work in the domain of data science. |
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(S1) Problem Solving – Numeracy and computational skills. |
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(S2) Problem Solving – Analysing facts and situations and applying creative thinking to develop appropriate solutions. |
Syllabus |
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DIFFERENTIAL CALCULUS (3 weeks) PROBABILITY THEORY (3 weeks) STATISTICS (3 weeks) |
Teaching and Learning Strategies |
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Teaching Method 1 - Lecture Teaching Method 2 - Tutorial Due to Covid-19, in 2021/22, one or more of the following delivery methods will be implemented based on the current local conditions. (b) Fully online delivery and assessment (c) Standard on-campus delivery |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
36 |
10 |
46 | ||||
Timetable (if known) | |||||||
Private Study | 104 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
(533) Final Exam. There is a resit opportunity. This is an anonymous assessment. | 2.5 | 60 | ||||
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
(533.1) Theory assignment 1. There is a resit opportunity [a part of the resit exam]. | 5 | 10 | ||||
(533.2) Theory assignment 2. There is a resit opportunity [a part of the resit exam]. | 10 | 10 | ||||
(553.3) Programming assignment There is a resit opportunity [a part of the resit exam] | 10 | 10 | ||||
(533.4) (Video) presentation. There is a resit opportunity [a part of the resit exam]. | 10 | 10 |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |