Python Machine Learning with Scikit-Learn Training | WSQ Courses

Originally published at:

Scikit Learn is the de facto Machine Learning package for Python. It consists of classification, regression, clustering, dimension reduction, model selection, and many data preprocessing functionalities. You can do many supervised and unsupervised machine learning with Scikit Learn.

This Machine Learning with Scikit Learn training aims to equip you with fundamental machine learning knowledge using such as classification algorithms and classification metrics, ensemble methods, regression and regularization, K-Means and Hierarchical Clustering and , feature reduction with PCA.

Course Highlights

  • Supervised Learning vs Unsupervised Learning
  • Analysing Classification Models with F1 Score and AUC
  • Multivariate Linear regression
  • Ridge and Lasso Regularization to reduce overfitting
  • Silhouette Analysis and Dendrogram for Clustering
  • Dimension Reduction with PCA


All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant Applications

Click the links below to apply. Note that you need to register the course first.

SkillsFuture Credit

For individuals, please submit your SkillsFuture Credit

SSG TG and AP Application

For companies, please fill up the SSG Training Grant Application Form after you have registered for this course

Please do not pay up front. We will advise you on the eligibility and nett fee after registration

If you prefer a WSQ funding, please checkout our WSQ Scikit Learn Machine Learning course.


Courses are provided by