CS818 - Big Data Fundamentals Online
TIMETABLE | TEACHING MATERIAL |
Credits | 10 |
Level | 5 |
Semester | Semester 2 |
Availability | |
Prerequisites | NA |
Learning Activities Breakdown | |
Assessment | The module is assessed 100% by individual assignment. |
Lecturer | Nur Muhamad Naim |
Aims and Objectives
The aim of this module is to endow students with an understanding of the new challenges posed by the advent of big data, as they refer to its modelling, storage, and access. It also ensures the students the key algorithms and techniques which are embodied in data analytics solutions and exposure to a number of different big data technologies and techniques, to show how they can achieve efficiency and scalability while also addressing design trade-offs and their impacts.
Learning Outcomes
After completing this class, participants will be able to:
- Understand the fundamentals of Python to enable the use of various big data technologies,
- Understand how classical statistical techniques are applied in modern data analysis,
- Understand the potential application of data analysis tools for various problems and appreciate their limitations.
Syllabus
- Introduction to Python;
- Quantitative methods for data analysis and knowledge extraction including classification, clustering, association rules, Bayesian approaches, and decision trees.
Recommended Reading
This list is indicative only – the class lecturer may recommend alternative reading material. Please do not purchase any of the reading material listed below until you have confirmed with the class lecturer that it will be used for this class.
Learning Python. Lutz, M. O’Reilly Media, Inc. 2013. ISBN-13: 978-1449355739 | Stocked at Amazon (Other retailers are available)
Last updated: 2023-09-14 14:39:36