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Advanced Certificate in Applied Data Science and Analytics (I) Module 5: Practicum using Tableau and Python

  • Analytics & Tech
  • Innovation & Business Improvement
Next Intake: 10 Jan 2026 (Sat)
  • Basic
  • SkillsFuture
  • Short Courses
  • This module is part of Advanced Certificate in Applied Data Science and Analytics (I)

This module is conducted online.

Next course starts on
10 Jan 2026 (Sat) See Full Schedule
Fee
SGD2,725* (as low as SGD317.50 after maximum funding) Learn More
Duration

Conducted over 6 Saturday mornings:

Session 1 : 2 hours
Sessions 2-5 : 3 hours each
Session 6 : 4 hours

Level
Basic

Who Should Attend

  • Ideal for non-data analysts in various industries using Excel for data work. Requires basic Tableau/Power BI skills or similar data handling exposure.
  • Enhances digital literacy for competent business or data analyst roles.

PREREQUISITES

This programme is structured to provide a comprehensive learning experience. Participants are required to complete the modules in the designated sequence to ensure a solid understanding of each topic before moving on to the next.

Overview

Having been introduced to diverse data science methodologies across the initial four modules, Module 5 will challenge participants to apply their newfound skills to real-world problems. Utilising dashboarding and predictive modeling techniques facilitated by tools such as Tableau and Python, participants will collaborate in groups. Each group will select datasets from various domains, analyse them, and present a comprehensive business case demonstrating their application of these techniques.

Learning Objectives

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

  • Gain exposure to real-world problems and apply skills acquired in the first four modules
  • Apply dashboarding and predictive modeling techniques with tools such as Tableau and Python in practical scenarios
  • Demonstrate proficiency in applying acquired skills across various domains and datasets
  • Showcase practical knowledge and skills in the application of data science methodologies

Assessment

As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.

Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.

Calculate Programme Fee

Click here for more information about SkillsFuture Credits (Not applicable for Company-sponsored participants)
For PSEA - Available only for Singapore Citizen below 31 (Not applicable for Company-sponsored participants)

Total Program Fee: SGD0.00

Fee Table

EMPLOYER-SPONSORED

PARTICIPANT PROFILE

SELF-SPONSORED

SME

NON-SME

Singapore Citizen < 40 years old

Permanent Resident

LTVP+

$817.50

(After SSG Funding 70%)

$317.50

(After SSG Funding 70%
+ ETSS Funding 20%)

$817.50

(After SSG Funding 70%)

Singapore Citizen ≥ 40 years old

$317.50

(After SSG Funding 70%
+ MCES Funding 20%)

$317.50

(After SSG Funding 70%
+ ETSS Funding 20%)

$317.50

(After SSG Funding 70%
+ MCES Funding 20%)

International Participant

$2,725

(No Funding)

$2,725

(No Funding)

$2,725

(No Funding)

All prices include 9% GST

Please note that the programme fees are subject to change without prior notice.

Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.

Self Sponsored

SkillsFuture Credit

Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.

This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.

Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).

Workfare Skills Support Scheme

From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.

Employer Sponsored

Enhanced Training Support for SMEs (ETSS)

  • Organisation must be registered or incorporated in Singapore
  • Employment size of not more than 200 or with annual sales turnover of not more than $100 million
  • Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
  • Trainees must be Singapore Citizens or Singapore Permanent Residents
  • Trainees must not be a full-time national serviceman
  • Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here. 

Please click here for more information on ETSS.

Absentee Payroll

Employers who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:

AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)

Intake Information

 

This module is conducted in-person.

Course

Dates

INTAKE 1

10 Jan -  14 Feb 2026 (Synchronous eLearning)
[Open for Registration]

Session Timing: 
Session 1: 10 Jan 2026 (9am-11am)
Session 2: 17 Jan 2026 (9am-12pm)
Session 3: 24 Jan 2026 (9am-12pm)
Session 4: 31 Jan 2026 (9am-12pm)
Session 5: 7 Feb 2026 (9am-12pm)
Session 6: 14 Feb 2026 (9am-1pm)

*Online registration will close 5 calendar days before the course start date

Trainers

Dr Rita Chakravarti
Chief Analytics Officer
SMART CONSULTING SOLUTIONS PTE LTD
Dr Rita Chakravarti
Chief Analytics Officer
SMART CONSULTING SOLUTIONS PTE LTD

Rita is in Data Science industry in more than 35 years and is known for her passion and versatility in applying Data Science in all kinds of business problems in Industrial Research, Insurance, Retail Banking and Telco. From 1999-2016 she has primarily focussed in the area of Banking both from Risk and Marketing perspective and an expert on bureau usage for risk management well conversant with usage of Data Science and DSAI tools in retail banking space. From 2014 onwards, she started taking active interest in academia and from 2016-2023 was heading the MTech Program (EBAC) in NUS-ISS. She was responsible for curriculum development and the growth of the programme. During this period the programme grew significantly and became the most popular discipline.

She did her PhD from University of Pittsburgh in Multivariate Analysis. During the early years of her career, she also taught in University of Pittsburgh, USA, University of Toronto, Canada and Northern Illinois University, USA.

She has extensive experience applying Data Science in banking sector, being the regional head (APAC) for Citibank, FICO and Experian.

Her area of specialisation are Risk/marketing Modelling, Multivariate Segmentation for customer management, Data and Tool Usage in Major Areas of Retail Banking, In-depth strategic understanding of usage of data and DSAI solutions in banking and other domains.

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