The Empower Program



Students will be taught the course “Machine Learning A-Z™”, which is the most popular course on the topic on Udemy, and is FutureSkills credit eligible. Note that we will use Python as the programming language and teach the first 6 Parts of the course, and we will augment the course with debates on business applications and ethics, discussions with entrepreneurs, and visits to innovation labs. 

The course will be taught twice a year in the two terms in every Polytechnic. Each course will be 15 weeks long and classes will occur over the weekend (3.5 hours/weekend) and instructors will hold office hours during the week.

Part 1 - Data Preprocessing

Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression

Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification

Part 4 - Clustering: K-Means, Hierarchical Clustering

Part 5 - Association Rule Learning: Apriori, Eclat

Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling

OCT 20 - FEB 23

Every Saturday
9.00am - 12.30pm


Ngee Ann Polytechnic



Empower is launching on Oct 20, 2018 in Ngee Ann Polytechnic and will be the lighthouse project with 25 girls. The pilot class is kept small to test the concepts before we scale it to all 5 Polytechnics in 2019.

The course will last 15 weeks and end on Feb 23 2019. Classes will take place at the Ngee Polytechnic campus while events will take place at SG Innovate. In addition, the girls will visit the innovation lab of one of our corporate partners.

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The role of the instructor is to facilitate discussion, explain concepts from the online course that are unclear to students, and to guide those who are struggling with in-class assignments.

The student to instructor ratio will be 15 - 1 in each course.

There will be minimum 2 instructors in every course: one has a background in computer science and AI, and the other who is a technologist and can explain the application of AI to business problems.

Instructors will carry out 3 anonymous surveys to get feedback from the girls on the quality of the course. A short final assessment will also be given to the girls.

Sample Instructors :

Theoretical AI Instructor: NUS adjunct lecturer, and founder of a blockchain-driven AI startup; NUS post-doc and current data scientist in a healthcare startup, focusing on machine learning for chronic disease progression.

Applied AI Instructor: Ngee Poly graduate working in banking sector.