Date: On Demand
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)
Assoc Prof Danny Poo
Assoc Prof Danny Poo
Assoc Prof Danny Poo brings with him 35 years of Software Engineering and Information Technology and Management experience. A graduate from the University of Manchester Institute of Science and Technology (UMIST), England, Dr Poo is currently an Associate Professor at the Department of Information Systems and Analytics, National University of Singapore. Prior to joining the University, Dr Poo was with the System Operations at DBSBank, Singapore.
A Steering Committee member of the Asia-Pacific Software Engineering Conference, Dr Poo is actively involved in Information Management and Healthcare Analytics research. A well-known speaker in seminars, Dr Poo has conducted numerous in-house training and consultancy for organizations, both locally and regionally. Dr Poo is the author of 5 books on Object-Oriented Software Engineering, Java Programming language and Enterprise JavaBeans.
Dr Poo notable teaching credentials include:
- Data Strategy
- Data StoryTelling
- Data Visualisation
- Data Analytics
- Machine Learning
- Data Management
- Data Governance
- Data Architecture
- Capstone Projects for Business Analytics
- Software Engineering
- Server-side Systems Design and Development
- Information Technology Project Management
- Health Informatics
- Healthcare Analytics
- Health Informatics Leadership.
Industry Credentials
- Deutsche Bank
- Gemplus
- Micron
- NCR
- PIL
- PSA
- Rhode-Schwarz
- Standard Chartered Bank
- ST Electronic
- Monetary Authority of Singapore
- Infocomm Development Authority
- National Library Board
- Ministry of Manpower
- Nanyang Technological University
- Nanyang Polytechnic
- National University Hospital.
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