NUS
 
ISS
 

Analytics for Commercial Excellence

Overview

Reference No TGS-2022010725
Part of Graduate Certificate in Specialised Predictive Modelling & Forecasting
Duration 4 days
Course Time 9:00am to 5:00pm
Enquiry Please contact ask-iss@nus.edu.sg for more details.

As companies increasingly integrate data across functions, the boundaries between marketing, sales and operations have been blurring.  This allows them to find new opportunities that arise by aligning and integrating the activities of supply and demand to drive integrated and sustainable commercial excellence.

This course will leverage the combined strengths of predictive and prescriptive techniques across disciplines (e.g. statistical and machine learning, mathematical optimisation, simulation and modelling, deep learning and AI etc.) to derive actionable and timely insights to drive marketing, salesforce and operations excellence for integrated and sustainable commercial excellence.

This course is part of the Data Science Series offered by NUS-ISS. The course provides an intermediate pathway to the ISS portfolio in the Data Science Graduate Certificate in Specialised Predictive Modelling & Forecasting syllabus that will be one of the graduate certificates in analytics, stackable towards a Masters of Technology in Enterprise Business Analytics.

Upcoming Classes

Class 1 13 Sep 2025 to 04 Oct 2025 (Full Time)

Duration: 4 days

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



Key Takeaways

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

  • Introduction to analytics, trends and developments for integrated and sustainable Commercial Excellence
  • Learn and apply Statistical and Simulation Techniques for business systems modelling
  • Implement marketing and optimisation techniques for driving salesforce effectiveness and channel optimisation.
  • Apply sales analytics, demand management and capacity analytics for resource planning, allocation and optimisation
  • Apply deep learning approaches for facilitating the development of sustainable systems, such as a computer-vision-assisted sustainable development.



Who Should Attend

It is applicable for professionals engaged in the following areas:

  • Commercial Excellence/Strategy/Operations/Intelligence & Analytics
  • Product/Pricing Analyst
  • Sales/Marketing Operations or Analyst
  • Revenue Management/Operations Analyst
  • Business Intelligence/Analytics/Planning and Strategy Analyst

Pre-requisites

  • Participants with some prior years of experience working within planning teams in an organisation will benefit more from the course.
  • Participants also need to have a strong interest and knowledge in basic predictive modelling and be familiar with R/Python.
  • Participants are required to have completed the Statistics Bootcamp II and Predictive Analytics - Insights of Trends and Irregularities prior to attending this course.

NUS-ISS also offers a range of other basic courses in Data Analytics Process and Best Practice II, Statistics Bootcamp II and Predictive Analytics - Insights of Trends and Irregularities for participants new to Data Science.


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:
• Excel - Solver
• R & R studio
• Python (Anaconda)
• JMP



What Will Be Covered

This course will cover:

  • Introduction to analytics, trends and developments for integrated and sustainable Commercial Excellence
  • Capacity Analytics for Resource Planning, Allocation and Optimisation
  • Sales Analytics for In-store Operational Excellence
  • Statistical and Simulation Techniques for integrated and sustainable commercial excellence
  • Deep Learning and AI for development of sustainable systems



Fees & Subsidies

Fees for 2024
  Full Fee Singaporeans & PRs
(self-sponsored)
Full course fee S$3600 S$3600
ISS Subsidy  - (S$360)
Nett course fee S$3600 S$3240
9% GST on nett course fee S$324 S$291.60
Total nett course fee payable, including GST S$3924 S$3531.60
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

Register now and uplift organisational commercial excellence via various analytics & AI tools and techniques.



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.




Course Resources

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