Dates: 25 Sep, 26 Sep, 27 Sep 2023 | 9am-5.30pm | Classroom Learning
Duration: 3 Days
Course Overview
Machine learning is a branch of Artificial Intelligence which makes use of sample data known as training data to build a model for making predictions or decisions without being explicitly programmed to do so. It has been applied in many applications such as email filtering, text analysis, sales forecasting, digital marketing, computer vision, healthcare, etc. where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks. In this course, participants will learn the fundamental concepts in Machine Learning. These include Supervised and Unsupervised Learning methods such as Linear Regression, Logistics Regression, Support Vector Machines, K-Nearest Neighbours, K-Means and Hierarchical Clustering. This course teaches how to use Python to create Machine Learning applications.
This module is part of Professional Certificate in Machine Learning Using Python.
Course Objectives
This course aims to:
- Provide participants with a strong foundation in advanced analytics methods.
- Provide participants with the necessary knowledge to appreciate the proper application of advanced analytics methods in business applications.
- Teach participants the use of Python for creating Machine Learning applications.
At the end of the course, participants will be able to:
- Understand various machine learning methods for classifying and clustering data.
- Use Python to implement Machine Learning methods in business applications.
Who Should Attend
Managers, Research Analysts, Software Engineers
Prerequisites
Polytechnic diploma and have knowledge in Python programming.
Course Convener
(Click their photos to view their short biographies)
Dr Ai Xin
Dr Ai Xin
Dr Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS). She has many years’ experience on teaching Artificial Intelligence and Data Science courses, e.g. machine learning, deep learning, data mining and etc.
She graduated from NUS with a PhD degree on Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks.
She worked in BHP Billiton Marketing Asia for eight years and gained a lot of industry experience through different functions, e.g. risk management, supply chain management, sales and marketing planning and etc.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Code:
TGS-2022011025
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older