Course Information

  • Sessions 2 days
  • Duration 16 hrs
  • Level Intermediate
  • Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Skills Framework

TSC Title
Data Analytics
TSC Code
ICT-BIN-4104-1.1

Learning Outcomes

By end of the course, learners should be able to:

  • LO1: Interpret data patterns to extract business insights for organization benefits and growth.
  • LO2: Manage data science projects and customize data models.
  • LO3: Manage the capacity to run complex data mining models for exploring data sets.
  • LO4: Communicate data science results, making recommendations using data modelling methods.

Course Brochure

Certification

  • Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.
  • OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - Microsoft Azure Data Scientist Associate (DP-100)

Course Code: TGS-2023036642
  • WSQ
  • SFC
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES
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What's This Course About

Unlock your potential in the world of data science with Microsoft Azure Data Scientist Associate (DP-100) course. This course provides a comprehensive overview of how to design and implement data science solutions on the powerful Azure platform. Whether you are a beginner or an experienced professional, this course will help you gain a deeper understanding of Azure's tools and techniques, enabling you to solve complex business problems with innovative solutions.

This course focuses on practical applications, enabling you to handle real-world scenarios effectively. You will learn how to manage data science projects, interpret data patterns, run complex data mining models, and communicate the results effectively. By the end of the course, you'll be equipped with the skills necessary to pass the DP-100 exam and become a certified professional, enhancing your career prospects in the exciting field of data science.

Bonus: Free Practice Exams

Get exam-ready on our Practice Exam Portal — train in realistic Practice Mode and timed Exam Mode, then retake them as many times as you like before the real exam.

Start Practising →

WSQ Funding

Full Fee $800.00 Before GST
GST $72.00 9% of fee
Baseline Nett $472.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $312.00 SG age 40+ · 70% funded
SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.

View on SkillsFuture for Business

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used.

Direct Application on SkillsFuture Portal

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year.

Submit UTAP Claim

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

Check PSEA Eligibility

  • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form, then submit the completed form to us:

PSEA Withdrawal FormSubmit PSEA Form

Funding Validity

Funding for this course is valid from 18 Aug 2023 to 17 Aug 2027. Register and complete the course within this period to qualify for funding support.

Course FeeBefore Funding

$800.00 (GST-exclusive)
$872.00 (GST-inclusive)

Course Date

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

Course Details

What You'll Learn

LU1 Work with Data using Azure Machine Learning

  • Topic 1 Explore the Azure Machine Learning workspace
  • Topic 2 Work with data in Azure Machine Learning

LU2 Manage Data Science Projects and Customize Data Models

  • Topic 3 Automate machine learning model selection with Azure Machine Learning

LU3 Run Data Model and Manage Capacity

  • Topic 4 Train models with scripts in Azure Machine Learning
  • Topic 5 Optimize model training in Azure Machine Learning

LU4 Recommendations for Model Deployment

  • Topic 6 Deploy and consume models with Azure Machine Learning

Assessment

  • Written Exam
  • Practical Exam

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Year Group : 21-65 years old

Minimum Software/Hardware Requirement

Software:

You need to sign up a Azure account (Credit Card is required).

Hardware: Windows and Mac Laptops

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity. 

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee Employer Sponsored Trainee
  • Singapore Citizens or Singapore Permanent Residents
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.
  • Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

 SkillsFuture Credit: 

  • Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

 PSEA:

  • To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
  • Scroll down to "Keyword Tags" to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.  
  • And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA. 
  • Not all courses are eligible for PSEA funding.

 Absentee Payroll (AP) Funding: 

  • $4.50 per hour, capped at $100,000 per enterprise per calendar year.
  • AP funding will be computed based on the actual number of training hours attended by the trainee.

 SFEC:

  • If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SWDA would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
  • Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
  • SkillsFuture Enterprise Credit (SFEC) Microsite 

 

Steps to Apply Skills Future Claim

  • The staff will send you an invoice with the fee breakdown.
  • Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
  • Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
  • Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The  SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

  • Log in to your U Portal account to submit your UTAP application upon completion of the course.

Note

  • SWDA subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
  • All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
  • An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
  • UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
  • UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

  1. The candidate has the right to disagree with the assessment decision made by the assessor.
  2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
  3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
  4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
  5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
  6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
  7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
  8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
  9. The assessor can help the candidate with writing and lodging the appeal.
  10. he assessment manager will collect information from the candidate & assessor and give a final decision.
  11. A record of the appeal and any subsequent actions and findings will be made.
  12. An Assessment Appeal Panel will be formed to review and give a decision.
  13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
  14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
  15. Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Job Roles

  • Data Scientist
  • Azure Data Engineer
  • Azure Solution Architect
  • Machine Learning Engineer
  • Cloud Data Scientist
  • Data Analytics Manager
  • Cloud Solution Consultant
  • Azure DevOps Engineer
  • AI Developer on Azure
  • Data Science Consultant
  • Cloud Infrastructure Specialist
  • Big Data Engineer on Azure
  • Data Platform Specialist
  • Machine Learning Operations (MLOps) Engineer
  • Cloud Application Developer

Trainers

Trainers

Sanjiv i is an ACTA certified experienced leader with a proven track record in business / finance consulting and in developing i) business intelligence (BI) solutions ii) data analytics/analysis solutions and iii) IOT lead BI solutions. Sanjiv's goal through Prudentia Consulting, is to promote the simple joy and excitement of actively using the Microsoft Platform. He believes that the agility afforded by the Microsoft platform helps businesses get time back for deeper business thinking and to spend more time with their end customers Sanjiv has rich experiences in diverse/complex high-tech businesses, turn around environments and strategic transformations. His functional expertise is in sales analytics, financial planning and analysis, engineering and program management. He has worked across discrete manufacturing, professional services and higher education verticals. He also has a working knowledge of equities portfolio management within the financial services domain.Sanjiv is the CEO of Prudentia Consulting, an organization committed to promoting the active usage of the Microsoft Platform. Prior to this, he has worked at Microsoft (US & APAC: 9.2 years), Cognizant Tech Solutions (3.3 years), Yazaki North America (8 years) and until recently at Oracle. Here are a few of his BI/analytics projects driven at scale: Built APAC wide BI dashboard using the Power BI umbrella tool set (Power BI online, Power BI desktop and Power Pivot) and a KPI lake (SQL DB), Helped develop key KPIs – identified key KPIs and helped land this in the DB, Developed a budget audit tool that captured budget inputs from a host of countries across the globe, Developed a business unit P&L reporting tool (functional architecture) in Business Objects for the world-wide financial planning and analysis team.

Alec Tan is a data and cloud professional specializing in Microsoft Azure services, advanced analytics, and applied machine learning. With extensive training experience in data fundamentals, SQL, and cloud-based AI solutions, he has supported professionals across industries in adopting Azure for modern data science workflows. His expertise spans Azure SQL, Cosmos DB, and Azure Machine Learning Studio, giving him both breadth and depth across the Azure data and AI stack.
In this program, Alec focuses on guiding learners through DP-100 core skills, including building ML pipelines, performing model training, and deploying AI solutions on Azure. His learner-focused approach emphasizes hands-on labs, ensuring participants can translate theory into practice. By bridging machine learning fundamentals with Azure’s cloud ecosystem, Alec empowers learners to build scalable and production-ready AI models.

Kishan Raaj is an IT trainer and consultant specializing in Microsoft Azure, data analytics, and Python programming. With extensive experience delivering SkillsFuture-accredited programs, he has trained professionals in cloud computing, business intelligence, and AI applications. His ability to simplify complex technical concepts makes him highly effective in equipping learners from diverse backgrounds to adopt AI and data science workflows.
In DP-100 training, Kishan emphasizes practical application of Azure Machine Learning, helping learners build models, run experiments, and deploy solutions in cloud environments. His teaching combines structured explanations with applied case studies, enabling participants to connect AI concepts with business outcomes. His approachable style ensures learners not only gain certification readiness but also the skills to apply Azure ML confidently in workplace projects.

Quah Chee Yong (QCY) is a WSQ ACLP-certified trainer and data science practitioner with extensive expertise in AI, NLP, and predictive analytics. He has served as Data Science Training Lead for SAP’s SGUnited program, designing and delivering training in machine learning, R, Python, and AI adoption. His industry experience includes building digital assistants, recommender systems, and data-driven business solutions that leverage machine learning pipelines and knowledge representation.
In this course, QCY guides participants through the full Azure Machine Learning workflow, from data ingestion and model training to evaluation and deployment. He emphasizes responsible AI principles alongside technical practices, ensuring learners understand both the ethical and operational dimensions of applied AI. His blend of academic and practical expertise enables professionals to harness DP-100 skills effectively in business and research contexts.

Truman Ng is a highly certified ICT and infrastructure professional with more than 20 years of experience in networking, cybersecurity, and enterprise systems. He holds certifications including PMP®, HCIE®, and ACTA, and has trained professionals in Linux, DevOps, RPA, Docker, and cloud computing. With hands-on expertise in IT infrastructure, automation, and data workflows, he brings a strong applied perspective to cloud-based AI adoption.
In Azure Data Scientist Associate training, Truman focuses on integrating AI model development with enterprise IT environments. He guides learners through deploying Azure ML models securely and efficiently, ensuring that they can scale solutions in organizational contexts. His practical, infrastructure-driven approach complements data science workflows, giving participants the skills to manage AI projects from both technical and operational perspectives.

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