This module covers concepts such as Supervised and Unsupervised Learning. You will learn to use open source Python libraries like Scikit-learn, Pandas, as well as Numpy to preprocess datasets, train, test and evaluate different Machine Learning (ML) models. Choose between ML models such as Linear Regression, k-NN, Naïve Bayes and K-Means to solve problems through regression, classification and/or clustering.
Upon completing the module, you will be able to explain the essential principles of machine learning, and possess hands-on experience in building, training, validating and deploying machine learning models using Python.
Machine Learning Fundamentals is a module selected from the Specialist Diploma in Applied Artificial Intelligence. It enables you to either reskill or upskill without the need to pursue a full specialist diploma. As this is a stackable course, you may choose to complete the remaining modules within the validity period of 2 years to receive the full Specialist Diploma qualification.
Applicants should possess a relevant (Business, Engineering, or Technology) local polytechnic Diploma, ITE Technical Diploma / Technical Engineer Diploma / Work-Study Technical Diploma or Degree.
Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least five years of relevant working experience or supporting evidence of competency readiness. Suitable applicants who are shortlisted will have to go through an interview and/or entrance test. The polytechnic reserves the right to shortlist and admit applicants.
Conditional Offer
Graduating students (in final semester) from a local polytechnic or Institute of Technical Education (ITE) may apply for the programme.
Click here for more information on how to apply for the programme and receive a Conditional Offer.
Please click on the "Register" button to view the updated course schedule and fees on the Skills Training & Enhancement Portal (STEP).