This short course provides participants with a practical approach on how data can be used to make business decisions and drive performance using drag-and-drop visual machine learning tools.
- Perform data mining using the Cross-Industry Standard Process for Data Mining (CRISP-DM) model
- Distinguish between Supervised and Unsupervised machine learning techniques and tasks
- Build predictive classification and regression models and evaluate model performance
- Perform parameter tuning, model selection, feature selection techniques to improve model performance
- Apply feature engineering techniques to build simpler and better generalisation models
Classroom: 16/08/2021 to 18/08/2021
Synchronous e-learning: TBC
This course consists of 1 modules:
This course will be conducted in an interactive manner where participants will be engaged in discussions and hands-on practices using scenarios that were contextualised from real business settings.
- Introduction to machine learning
- Supervised and unsupervised machine learning techniques
- Model evaluation, enhancements and ensemble techniques
A certificate of Performance will be awarded to participants who achieve at least 75% attendance and pass all required assessment(s).
A certificate of Participation will be awarded to participants who meet the 75% attendance requirement but did not pass all required assessment(s).
Basic statistics knowledge preferred but not necessary
|Applicants / Eligibility||Fees|
|Singapore Citizens (SC) below the age of 40 years||$609.90|
|Singapore Citizens (SC) aged 40 and above||$229.90|
|Singapore Permanent Residents (PR)||$609.90|
|Enhanced Training Support for SME Scheme (for SC & SPR)||$229.90|
|Full Course Fee||$2033.00|