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Short Course

Azure Data Lake and Data Streaming

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
To be advised2Classroom LearningTGS-2024044675
To be advised2Synchronous e-LearningTGS-2024045532

Course Overview

This course teaches learners the core principles and advanced techniques required to design, implement, and manage big data processing architectures on Azure. Participants will learn Azure Data Lake and Data Streaming concepts. Participants will learn how to run queries on serverless Structured Query Language (SQL) pools and perform data engineering with Azure Apache Spark Pools. Participants will gain knowledge on streaming data and managing a running job. This course provides real-world scenarios and ensures 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:

  • Run interactive queries using Azure Synapse Analytics serverless SQL pool
  • Perform data engineering with Azure Synapse Apache Spark Pools
  • Explore Azure Data Lake Storage to make processing Big Data analytical solutions more efficient
  • Set up a stream analytics job to stream data and manage a running job
  • Acquire hands-on practice in Azure Labs

Who Should Attend

Data analysts, data engineers and managers who want 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

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