Key Takeaways
- Demonstrate understanding of descriptive and inferential statistics and articulate their relevance in business decision-making.
- Analyse data for central tendencies, variability, outliers, and trends using visual tools such as histograms and box plots, supported by GenAI-generated explanations.
- Conduct linear and logistic regression to uncover predictive insights and interpret model outputs with the aid of GenAI tools.
- Use decision trees and logistic regression to solve classification problems and evaluate model performance with GenAI assistance.
- Apply clustering algorithms to segment customers and construct actionable profiles using GenAI-supported analysis.
- Test and enhance model robustness through GenAI-driven diagnostics and recommendations.
- Use GenAI platforms to query datasets, generate visual narratives, and simulate human-AI collaboration in business contexts—without requiring coding expertise.
Who Should Attend
This course is tailored for business professionals, particularly those without formal training in statistics or coding who seek to become more data-literate and AI-fluent. It is ideal for mid-level managers, analysts, and functional specialists in areas such as marketing, HR, operations, and finance, who regularly work with data but feel unprepared to interpret or apply it confidently.
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
|
What Will Be Covered
- Data Understanding: Build a strong grounding in business analytics by learning key statistical concepts, data types, and how analytics supports structured problem-solving using frameworks like CRISP-DM. Understand how data is generated, shaped, and prepared for analysis.
- Statistical Analysis & Inference: Develop the ability to draw meaningful conclusions from data using sampling techniques, confidence intervals, and hypothesis testing, including comparisons across groups using ANOVA.
- Correlation & Regression analysis: Understand how variables relate to one another through correlation and regression, and learn how to build and interpret simple models for business insights.
- Model Evaluation & Validation: Gain the skills to assess the quality and reliability of analytical models by evaluating performance metrics, statistical significance, and the robustness of results.
- Foundational machine learning approaches: Explore classification using decision trees and segmentation using clustering, to uncover patterns and support data-driven decision-making.
Fees & Subsidies
SkillsFuture Singapore (SSG) Funding 2026 (Effective 1 July)
| Fee Component | Full Course Fees | Singapore Citizens & PRs Aged 21 Years and Above (70% Funding Support) | Singapore Citizens Aged 40 Years and Above (90% Funding Support) | Enhanced Training Support for SMEs (ETSS) (90% Funding Support) |
|---|
| Full Course Fee | S$3,800.00 | S$3,800.00 | S$3,800.00 | S$3,800.00 |
| SSG Funding | - | S$2,660.00 | S$2,660.00 | S$2,660.00 |
| Nett Course Fee | S$3,800.00 | S$1,140.00 | S$1,140.00 | S$1,140.00 |
| 9% GST on Nett Course Fee | S$342.00 | S$102.60 | S$102.60 | S$102.60 |
| Additional Funding if Eligible Under Various Schemes | - | - | S$760.00 | S$760.00 |
| Total Nett Course Fee Payable, Including GST | S$4,142.00 | S$1,242.60 | S$482.60 | S$482.60 |
|---|
Note:
- SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
- 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.
- SME fees are applicable only to participants who are sponsored by small and medium enterprises.
- SSG funding is subjected to availability.
Certificate
The ISS Certificate of Completion will be issued to participants who have attended at least 75% of the course and pass the required assessments.
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.