NUS
 
ISS
 
NUS ISS

Predictive Analytics - Insights of Trends and Irregularities

Overview

Reference No TGS-2020001431
Part of Graduate Certificate in Business Analytics Practice
Duration 5 days
Course Time 9am-5pm
Enquiry Please contact ask-iss@nus.edu.sg for more details.

There has been a growing demand for business analytics, particularly in recent years, and this trend is expected to continue. Predictive analytics stands out as a crucial component within business analytics. It leverages Artificial Intelligence (AI) and machine learning (ML) to extract insights from data and forecast future trends and behavioural patterns in businesses. Essentially, predictive analytics provides actionable business insights by analysing extensive historical data. It has found widespread application across various industries such as banking, insurance, telecommunications, retail, travel, and healthcare, significantly impacting planning and decision-making processes. Many companies are turning to predictive analytics to enhance competitiveness and outperform rivals.

This course aims to equip participants with the necessary knowledge and skills to effectively utilise AI and ML techniques for leveraging business data. Participants will learn to identify trends and anomalies in data and use them for predictive analysis, ultimately enabling their companies to gain a competitive edge by becoming more proactive in business and marketing strategies, leading to cost reduction and increased return on investment.

The course's objective is to empower participants with the concepts, methods, and techniques of predictive analytics using AI and ML. Through the many practice hands-on workshops, participants will gain practical experience in applying predictive modeling techniques to real-life business scenarios. While the course assumes some familiarity with statistical concepts like regression and logistic regression, it will review these topics to reinforce understanding. For participants lacking prior statistical knowledge, it is strongly recommended to attend the Statistics Bootcamp II before enrolling in this course.

This course is part of the Data Science and Graduate Certificate in Business Analytics Practice Series offered by NUS-ISS.

Upcoming Classes

Class 1 23 Jun 2025 to 27 Jun 2025 (Full Time)

Duration: 5 days

When:
Jun:
23, 24, 25, 26, 27
Time:
09:00am to 05:00pm

Class 2 06 Sep 2025 to 04 Oct 2025 (Full Time)

Duration: 5 days

When:
Sep:
06(Sat), 13(Sat), 20(Sat), 27(Sat)
Oct:
04(Sat)
Time:
09:00am to 05:00pm


Key Takeaways

At the end of the course, participants will be able to:



Who Should Attend

This course is for: 

  • IT professionals aiming to harness AI and ML methods for implementing predictive analytics to enhance business processes and decision-making.
  • Data/business analysts looking to enhance their expertise with AI and ML to gain insights and add value to their recommendations in business analytics.
  • Domain specialists and individuals embarking on business analytics projects, integrating AI and ML methodologies.
  • Sales personnel requiring accurate demand/sales forecasting, employing AI and ML strategies.
  • Professionals responsible for inventory planning utilising AI and ML techniques.
Prerequisites 
  • Participants are required to have completed the Statistics Bootcamp II course prior to attending this course.
  • The course workshops are conducted in R or Python. If participants have strong knowledge and experience in statistics and have not attended the Statistics Bootcamp II course, you will be required to send your CV or transcript for review.


What to Bring

No printed copies of course materials are issued.
Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials.

If you are bringing a laptop, please see below for the tech specs:

 

Minimum

Recommended

Operating Systems

• Windows 7, 8, 10 or
• Mac OS

Laptop running the latest
version of either Windows or
Mac OS

System Type

32-bit

64-bit

Memory

8 GB RAM

16+ GB RAM

Hard Drive

256 GB disk size

 

Others

 • An internet connection – broadband wired or wireless
• Installation permissions (non-company laptops)
• Keyboard
• Mouse/Trackpad
• Display
• Power adapter (laptop battery might run out)

DirectX 10 graphics card for graphics hardware acceleration

 

Additional Software Requirements:
• R & R Studio
• Python (Anaconda)
• Google Colab
• JMP
• Excel - Analysis Toolpak


What Will Be Covered

  • Introduction to predictive analytics, including an overview of AI and ML concepts.
  • How to make predictions using multiple regression models
  • Times series modelling and applications
  • Introduction to logistic regression modelling
  • Predictive modelling using decision trees
  • Predictive modelling using neutral networks
  • Practical case studies and workshops conducted in R or Python


Fees & Subsidies

Fees for 2025
  Full Fee Singaporeans & PRs
(self-sponsored)
Full course fee S$4500 S$4500
ISS Subsidy  - (S$450)
Nett course fee S$4500 S$4050
9% GST on nett course fee S$405 S$364.50
Total nett course fee payable, including GST S$4905 S$4414.50
Note:
  1. All fees and subsidies are valid from January 2024, unless otherwise advised.
  2. All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
  3. From 1st January 2024, the GST will be increased to 9%.


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Certificate

Certificate of Completion
Participants have to meet a minimum attendance rate of 75% and are required to pass the assessment to be issued a Certificate of Completion.


Join Us

Unlock trend predictive power with AI and ML. Register now to stay ahead in business analytics.


Preparing for Your Course

NUS-ISS Course Registration Terms and Conditions

Find out more.

NUS-ISS and Learner’s Commitment and Responsibilities

Find out more.

WIFI Access

WIFI access will be made available to participants.

Venue

NUS-ISS
25 Heng Mui Keng Terrace
Singapore 119615

Click HERE for directions to NUS-ISS

In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

Course Confirmation

All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

General Enquiry

Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.



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