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Course Overview

This course aims to bridge and enhance the knowledge and skillsets of participants to enable them to enter the field of Big Data Management. While data analysts use data to provide business and predictive insights, big data management professionals help organisations to manage incredibly large volumes and varieties of data using appropriate technologies. Effective big data management helps companies locate valuable information, whether they are large sets of unstructured or semi-structured data, from various sources. Join this course to learn how you can leverage on big data management to provide a business and analytics ready data pipeline to create value for your organisation. 

 

On completion of the course, graduates will be able to:

 

  • apply appropriate methods and tools to acquire and manage large data sets from various sources;
  • apply appropriate methods and tools to visualize big data;
  • manage big data projects.

 

Graduates will also obtain Statement of Attainment (SOAs) under the Skills Framework (SF) for Infocomm Technology:

 

  • ICT-DIT-3001-1.1 Analytics and Computational Modelling
  • ICT-DIT-3006-1.1 Data Visualisation

Application/Entry Requirement

At least a Polytechnic Diploma or ITE Technical Diploma/Technical Engineer Diploma/Work-Learn Technical Diploma in a technology or IT-related course, or equivalent. 

 

Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least 5 years of relevant working experience or supporting evidence of competency readiness. Suitable applicants who are shortlisted may have to go through an interview and/or entrance test. The Polytechnic reserves the right to shortlist and admit applicants.

Who Should Attend

The intended target is at diploma graduates and Professionals, Managers and Executives (PMEs) who are keen to enter the field of Big Data Management.

What You'll Learn

To be awarded the Specialist Diploma, participants are required to complete a total of 2 Post-Diploma Certificates (PDCs). A certificate will be issued upon successful completion of each PDC.

Subject Code Subject
CBG1C01 Big Data Systems Architecture

This subject introduces students to the emerging data architectures driven by “Big Data” adoption. This subject will cover new paradigms of data systems within the realm of "Big Data," which evolved from Google, LinkedIn, and Facebook. The student will be exposed to the concepts and techniques that have driven Big Data adoption and compare these with traditional data store architectures such as structured databases and data warehouses. Emerging data architectures such as real- time and complex event processing tools will also be covered.

CBG1C02 Data Security Fundamentals

This subject covers data security as a quality control discipline for assessing, managing, using, improving, monitoring, maintaining, and protecting organisational information. The student will learn about concepts such as data security & access, data protection, data policies, business process management, and risk management surrounding the handling of data in an organisation.

Subject Code Subject
CBG1C03 Data Visualization Fundamentals

This subject covers graphing fundamentals, graphing properties and building dashboards for reporting purposes using relevant statistical modeling and analysis techniques. Topics covered include the preparation and analysis of visualized data to support managerial decision-making.

CBG1C04 Big Data Programming

This subject equips students with the knowledge and skills to program a data management application to manage big data. The subject will cover commonly used scripting languages (such as python) and how it can be used for big data collection and processing. Other languages for data integration and processing (such as R) will be covered as well.

Modes of Assessment

 

Coursework with no examinations.

Career Opportunities

Graduates can expect good employment prospects across many industries such as government, financial and banking institutions and consulting firms as Big Data Specialist / Engineer, Big Data Operations Specialists, Big Data Technical Support Specialist, Big Data Application Developer, Big Data Hadoop/ QA Tester.

 

Graduates can also look towards upgrading their knowledge and skills in further Continuing Education and Training (CET) and executive programmes offered by local Institutes of Higher Learning such as the National University of Singapore (NUS) Strategic Technology Management Institute which offers many National Infocomm Competency Framework (NICF) certified executive courses in Big Data or Business Analytics.

Course Schedule

Intake Info Application Period Course Duration

19 April 2021

02 November 2020 - 11 January 2021

1 Year

APPLY

Course Fees

Course Fee per Post-Diploma Certificate

Fee Type Total Fees
w GST
SME-sponsored Singapore Citizens & Permanent Residents S$291.72
Singapore Citizens aged 40 & above S$282.48
Singapore Citizens aged below 40 S$423.72
Singapore Permanent Residents S$1,142.76
Others & Repeat Students S$2,863.32

SkillsFuture Credit Approved. For more details, please click here


Course fees payable is based on per MC.

Course fees will be reviewed by MOE on an annual basis and adjusted accordingly.

MOE subsidy will not be applicable for students who repeat a module or semester.

 

With effect from 1 Jul 2020, the Workforce Training Scheme (WTS) will be replaced by Work Support Scheme (WSS), for more information, please visit:

https://www.wsg.gov.sg/programmes-and-initiatives/workfare-skills-support-scheme-individuals.html

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Course Contact

  • 67881212
  • 8.30 am to 6.00 pm (Mon to Thu)

    8.30 am to 5.30 pm (Fri)

    Closed on Sat, Sun & Public Holidays

  • Website: https://www.tp.edu.sg/tsa
  • Temasek SkillsFuture Academy
    Temasek Polytechnic
    East Wing Block 1A, 
    Level 3, Unit 81
    21 Tampines Ave 1
    Singapore 529757

  • Temasek Polytechnic reserves the right to alter the course, modify the scale of fee, amend any other information or cancel course with low enrolment.

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