Applied Analytics Using Predictive Modelling

Short Course

Applied Analytics Using Predictive Modelling

Programme Schedule	Duration (days)	Mode of Delivery	Programme Code
To be advised	3	Classroom Learning	TGS-2019507053

Course Overview

Modern predictive analytics uses data to model a specific domain, isolate key factors and use the models or algorithms built using this process to predict likely future outcomes from new data. Predictive analytics is not a new concept and businesses have been using decision trees and regression to help correlate and classify their data and make predictions.

Mathematical modeling tools are applied to data in order to generate predictions about an unknown fact, characteristic, or even event not yet available in the dataset. To put it simply, we use statistical techniques to derive sophisticated predictive models and algorithms from large data sets without requiring explicit programming.

This course covers the life cycle of the data mining project and the key concepts of various predictive analytics techniques. It focuses on performing predictive analytics using supervised and unsupervised machine learning models on an open-source programming platform and how to communicate the results to audiences.

Course Objectives

Course will enable participants to:

Understand how to embark on a data mining project
Understand the fundamental key concepts of various predictive analytics techniques
Acquire basic proficiency on popular data analytics tools such as R
Understand how to prepare data for doing various predictive analytics techniques
Apply predictive analytics using popular tools
Identify which predictive analytics approaches to use for different situations

Who Should Attend

Any working professional who is interested to learn concepts, methodologies, and techniques in predictive analytics to improve business processes, and/or keen to use R open-source programming platform for predictive modeling.

Prerequisites

At least a polytechnic diploma. Participants are recommended to have knowledge of the fundamentals covered in Descriptive Analytics.

Technical Requirements

Participants should have a windows system that supports R packages and libraries for the practice labs.

Reserve Your Seat Now

Chat with us

This programme is part of

Professional Certificate in Business Analytics

Types of Available Fundings

SkillsFuture Funding

SkillsFuture Credit

Enhanced Training Support

SFEC

UTAP

PSEA

Testimonials

Super excellent trainer! Dr Yeo is able to explain complicated technical terminology by using practical examples. It is indeed a pleasant and fruitful adult learning experience.

Instructors

Ms Samantha Sow

Programme Fees

	Singapore Citizens		Singapore PRs	Enhanced Training Support for SMEs	International Participants
	39 years old or younger	40 years old or older	Singapore PRs	Enhanced Training Support for SMEs	International Participants
Full Programme Fee	S$2,550.00	S$2,550.00	S$2,550.00	S$2,550.00	S$2,550.00
Less: SSG Grant Amount	S$1,785.00	S$1,785.00	S$1,785.00	S$1,785.00	-
Nett Programme Fee	S$765.00	S$765.00	S$765.00	S$765.00	S$2,550.00
9% GST on Nett Programme Fee	S$68.85	S$68.85	S$68.85	S$68.85	S$229.50
Total Nett Programme Fee Payable, Including GST	S$833.85	S$833.85	S$833.85	S$833.85	S$2,779.50
Less Additional Funding	-	S$510.00	-	S$510.00	-
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes	S$833.85	S$323.85	S$833.85	S$323.85	S$2,779.50

Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
Please note that all external funding for courses is limited in duration and subject to eligibility and availability.

Other Information

This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.

Ms Samantha Sow

Advanced Computing for Executives