Key Takeaways
At the end of the course, the participants will be able to:
Apply experimental design methods for concept testing, factor screening, rapid experimentation and optimisation for connected and sustainable products
Understand basic economic concepts and apply econometrics for product & pricing analysis
Learn and implement the decision science techniques for product and pricing optimisation for a typical business entity (Linear Programming, Non-Linear Programming, Integer Programming)
Apply the strategy and methods for inventory optimisation and simulation (Monte Carlo Simulation and Discrete Event Simulation)
Build data collection, analytics, and decision-making capabilities and solutions with IoT technologies
Integrate machine learning and analytics into edge computing to building a more connected world and perform decision-making
Who Should Attend
It is applicable for professionals engaged in the following areas.
Product Analyst
Pricing Analyst
Commercial Excellence Analyst
Sales/Marketing Analyst
Prerequisites
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)
What Will Be Covered
- Introduction to analytics, trends and developments for Product and Pricing Excellence
- Experimental design techniques for product innovation and optimisation
- Econometrics and Pricing Analytics
- Prescriptive Analytics and Decision Science Techniques
- Decision Science for Product and Price Optimisation
- Inventory Planning and Simulation
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:
- All fees and subsidies are valid from January 2024, unless otherwise advised.
- 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.
- From 1st January 2024, the GST will be increased to 9%.
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.
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.