Data Mining studies algorithms that allow computers to find patterns and regularities in data, perform prediction and forecasting, and generally improve their performance through interaction with data. It is regarded as the key element of a more general process called Knowledge Discovery that deals with extracting useful knowledge from raw data.
The process includes data selection, cleaning, coding, using different statistical and machine learning techniques, and visualization of the generated structures. The course provides students with an appreciation of the uses of data mining software in solving business decision problems. Students will gain knowledge of theoretical background to several of the commonly used data mining techniques and will learn about the application of data mining as well as acquiring practical skills in the use of data mining algorithms.
Learn In No Time
To enable learners to have an overall understanding of the landscape of Data Mining and Machine Learning.
To give the participants the very first steps towards forming hypothesis and doing predictive analytics, learning some of the classification and regression techniques in supervised learning.
It aims to equip participants with the basics of how supervised machine learning models work and how evaluation and optimization can be carried out.
To equip learners in understanding some of the preparation and visualisation techniques which is required for knowledge discovery into their data.
To further equip learners with knowledge on other unsupervised learning techniques, and rule-based mining also be taught.
Before embarking on the data science journey, organizations need to be equipped with the right skills and be data literate. This course walks through that journey of getting an organization ready.
It's time to upskill for the Industry 4.0