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 | Big Data Analytics | ||
Code | COMP529 | ||
Coordinator |
Dr DK Wojtczak Computer Science D.Wojtczak@liverpool.ac.uk |
||
Year | CATS Level | Semester | CATS Value |
Session 2022-23 | Level 7 FHEQ | First Semester | 15 |
Aims |
|
To introduce students to advanced methods and algorithms used in Big Data analytics. |
Learning Outcomes |
|
(LO1) Deep and systematic knowledge of algorithmic approaches for Big Data analysis and handling batch and streaming data. |
|
(LO2) Comprehensive and critical insight into the software environments that can be used to enable algorithms to scale up to analysis of large batch and streaming datasets. |
|
(LO3) Devising a most suitable algorithm for solving a Big Data problem |
|
(LO4) Demonstrating a critical awareness of current problems and research issues in the field of Big Data |
|
(S1) Numeracy/computational skills - Reason with numbers/mathematical concepts |
|
(S2) Communication (oral, written and visual) - Following instructions/protocols/procedures |
Syllabus |
|
Week 1: Introduction to Big Data, motivating real-world applications. |
Teaching and Learning Strategies |
|
Teaching Method 1 - Lecture 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 |
24 |
12 |
12 |
48 | |||
Timetable (if known) | |||||||
Private Study | 102 | ||||||
TOTAL HOURS | 150 |
Assessment |
||||||
EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
(529) Final Exam Written Exam There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 1 | 120 | 60 | ||||
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
(529.1) Assessment 1 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :1 | 18 | 20 | ||||
(529.2) Assessment 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Semester 1 | 18 | 20 |
Recommended Texts |
|
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |