Data Analytics Deployment & Performance Monitoring

Course Reference Number: CRS-N-0051114


Course Objectives

This course is the sequel to our Data Analytics for Business Analysts course, and is designed for IT business analysts and professionals to undertake data science consultancy or advisory roles for data analytics projects, to drive a deeper discernment in:
• Data-driven problem solving
• Connecting business problems to apply data science methods
• Examining critical success factors of data science projects
• Managing analytics projects (both the innovation cycle and deployment cycle)
• Methods of data extraction, cleansing and transforming raw data into analytics-ready data

It aims to equip participants with the knowledge and skills to:
• Experiment with data science capabilities and recognise its limitations
• Implement and manage the data science process for innovation and deployment cycles
• Provide advisory for and deliver high-quality data analytics projects

At the end of this course, participants will be able to:
• Get up to speed on analytics life cycle and move into data-driven problem solving
• Assess relevant data components for data exploration and insight discovery
• Distinguish model equation and outputs from modeling scripts
• Setup predictive analytics model with the right mix of features and functionality requirement
• Apply model performance monitoring metrics and method
• Design UI from user perspective
• Design and construct a model for predictive analytics and model performance monitoring


Day 1

• Introduction to Data Analytics Deployment and Performance Monitoring
• Starting the journey: data-driven problem-solving approach
• Model/algorithm storing, execution, and output data 

Day 2

• Predictive Analytics and Model Performance Monitoring  
• Workshop-style Learning


Python (Jupyter Notebook) and Power BI


Participants should have at least 2 years of working experience with the following data analytics knowledge in part or whole:
• Overview of data science techniques, process and technology
• Data science consulting skills
• Connecting business problems to data science
• Managing analytics projects (both innovation cycle and deployment cycle)
• Understand data science capabilities and its limitations
• Implement and manage the data science process for innovation and deployment cycles
• Advise and deliver high-quality data analytics projects

Who Should Attend

IT Business Analysts and professionals who would like a deeper dive into data analytics.

Mode of Training



Catherine Khaw

Catherine Khaw is an evangelist for data and analytics literacy at economy, organisational and individual levels. She is the founder of DNA Capitals which drives competitive advantage for organisations in all industries through taking full advantage of the opportunities which arise from digitization and big data. As a data and analytics evangelist, she is an active member of Tech Talent Assembly (TTAB) association which nurtures tech talents for lifelong employability, learning and sharing.
Catherine was formerly the Practice Chief of Analytics & Intelligent System at NUS Institute of Systems Science (NUS-ISS), where she imparted her experience and knowledge to graduate students, business leaders and ICT practitioners. She also continues to serve as adjunct lecturer and coach to NUS ISS students and short course participants.




2 Days 
9.00am – 5.30pm 


National University of Singapore
University Town

Fees & Fundings

International Participants


Incl. GST

Singapore Citizens (39 yrs old or younger)  or Singapore PRs


Incl. GST

Singapore Citizens
(40 yrs or older)


Incl. GST

Enhanced Training Support for SMEs


Incl. GST

Singapore Citizen1
39 years old or younger
Singapore Citizen1
40 years or older eligible for MCES2
Singapore PRs Enhanced Training
Support for SMEs3
Full Programme Fee S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00
SkillsFuture Funding
(Refer to Funding Page for Claim Period)
- (S$1,470.00) (S$1,470.00) (S$1,470.00) (S$1,470.00)
Nett Programme Fee S$2,100.00 S$630.00 S$630.00 S$630.00 S$630.00
7% GST on Nett
Programme Fee
S$147.00 S$44.10 S$44.10 S$44.10 S$44.10
Total Nett Programme
Fee Payable, Incl. GST
S$2,247.00 S$674.10 S$674.10 S$674.10 S$674.10
Less Additional Funding if
Eligible Under Various Scheme
- - (S$420.00) - (S$420.00)
Total Nett Programme Fee, Incl. GST,
after additional funding from the various funding schemes
S$2,247.00 S$674.10 S$254.10 S$674.10

  1. All self-sponsored Singaporeans aged 25 and above can use their $500 SkillsFuture Credit to pay for the programme. Visit to select the programme. 
  2. Mid-Career Enhanced Subsidy (MCES) - Singaporeans aged 40 and above may enjoy subsidies up to 90% of the programme fee. 
  3. Enhanced Training Support for SMEs (ETSS) - SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the programme fee. For more information, visit
  4. Eligible organisations (excluding government entities) may apply for the absentee payroll funding via SkillsConnect at for Singaporean/permanent resident participants attending the programme during working hours. The absentee payroll funding is computed at 80% of hourly basic salary capped at $4.50 per hour or $7.50 per hour for SME. For more information, visit
  5. Eligible individuals may apply for training allowance capped at $6/hr under the WSS scheme, visit- for more information on WSS.
  6. NTUC Training Fund (SEPs) – All self-employed (i.e. freelancers and sole-proprietors-with-no-employee) Singaporeans and Permanent Residents are eligible to apply for the NTUC Training Fund (SEPs) from NTUC’s Employment and Employability Institute (e2i). Click here for more information.
NTUC members enjoy 50% of the unfunded course fee support for up to $250 each year for courses supported under UTAP (Union Training Assistance Programme). Terms and Conditions apply. Please visit
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03 November 2020