Facebook-f Linkedin Instagram Youtube Tiktok
Short Course

Azure Data Storage and Data Pipelines

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
To be advised2Classroom LearningTGS-2024044677
To be advised2Synchronous e-LearningTGS-2024044676

Course Overview

This course teaches learners the core principles and advanced techniques required to design, implement, and manage data processing architectures on Azure. Participants will learn Azure compute and storage options for data engineering workloads. Participants will learn how to transform data with Azure Data Factory or Azure Synapse Pipelines. This course provides real-world scenarios and ensure learners gain practical and develop essential skills through guided lab practices in the Azure portal. At the end of this course, participants will be prepared to pursue the DP-203 certification independently should they choose to do so.

Course Objectives

This course will enable participants to:

  • Understand Azure compute and storage options for data engineering workloads
  • Transform Data with Azure Data Factory or Azure Synapse Pipelines
  • Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
  • Acquire hands-on practice in Azure Labs

Who Should Attend

Data analysts, data engineers and managers who wants to leverage cloud based data integration, orchestration, and optimization

Prerequisites

Minimum Polytechnic Diploma Level

Contact Us

Types of Available Fundings

  • SkillsFuture Credit

    • Instructors


    Ms Samantha Sow

    Ms Samantha Sow

    Ms. Samantha Sow is currently a Senior Lecturer in the department of Information Systems and Analytics at the National University of Singapore (NUS). She has over 8+ years of experience in Business Analytics and Data Science and she conducts training for both government agencies and corporate clients. Before joining NUS, she lectures at Temasek Polytechnic, teaching Business Analytics and Data Science to professionals, managers and executives (PMEs). Prior to being an academia, Samantha worked in the research and development at Infineon Technologies. Her research and project areas include Business Analytics, Data Mining, Predictive and Prescriptive Analytics. She has a passion for engaging and inspiring participants to enhance their workplace analytics capabilities and increase business intelligence quotient within their organisations. Her interests lie in the applications of data analytics, predictive modelling and optimization techniques to derive actionable insights for commercial effectiveness. She is familiar with typical analytics tools such as Python, R, and SAS, SPSS and Tableau. She also has working knowledge in the area of Analytics, Data Science and Machine Learning. Samantha completed her Master of Education from University of Sheffield and graduated from the National University of Singapore with a Bachelor’s in Engineering, First Class Honours. She has also completed THEC (Teaching in Higher Education) and ACTA (Advanced Certificate in Training and Assessment). She is a member of the adult associate educator (AEN) by Institute for Adult Learning (IAL), Singapore. Her certifications include: Microsoft Certified Azure Data Scientist Associate. Microsoft Certified Data Analyst Associate. SAS Certified Predictive Modeller in SAS Enterprise Miner. Tableau Certified Desktop Specialist.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Programme Fee S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00
    Less: SSG Grant Amount S$1,330.00 S$1,330.00 S$1,330.00 S$1,330.00 -
    Nett Programme Fee S$570.00 S$570.00 S$570.00 S$570.00 S$1,900.00
    9% GST on Nett Programme Fee S$51.30 S$51.30 S$51.30 S$51.30 S$171.00
    Total Nett Programme Fee Payable, Including GST S$621.30 S$621.30 S$621.30 S$621.30 S$2,071.00
    Less Additional Funding - S$380.00 - S$380.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$621.30 S$241.30 S$621.30 S$241.30 S$2,071.00
    1. Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
    2. GST shall apply at prevailing rates.
    3. Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.

    Connect with us

    11 Research Link
    COM 3, #B1-07
    Singapore 119391
    Telephone: +65 6516 5523
    Email: soc-ace@nus.edu.sg

    Facebook-f Linkedin Instagram Youtube Tiktok

    About us 

    Programmes for individuals     

    Solutions for organisations    

    online learning     

    terms and conditions      

    Course catalogue     

    Scroll to Top