Data Mining and Big Data
The purpose of this course is to provide students with an introduction to data mining and how to best handle big data. Most applied research relies on data that is only getting larger and more complicated. Researchers have to first clean, manage and mine the data to better understand any existing relationships and guide analysis. This course is aimed towards research and public policy applications.
This module can be taken alone, or as part of a PG Certificate, PG Diploma or Full Masters Program.
Understand and interpret Different data structures.
The coding dos and don'ts.
Looping, Data Visualisation, Data Mining and Machine Learning.
By the end of this course, participants should have knowledge and ability to:
Use statistical and other packages effectively, presenting, interpreting and analysing information in numerical form.
Understand big data basics (data storage, quality, etc.)
Communicate and present complex arguments in oral and written form with clarity and succinctness.
Apply basic machine learning algorithms.
By the end of this course, students should be able to:
Understand Data movement and manipulation and how to present complex data in graphs and plots that are easy to follow.
Data Mining and Big Data Management is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.
The total number of contact hours is 15 hours. This leaves 85 hours for private study.
This module consists of 2- hour lectures per day, for 5 consecutive days, plus a 1 - hour tutorial per day.
There will be optional clinics on the last day of the course.