Home > Courses > Big Data Technologies

Big Data Technologies

Name: Big Data Technologies
Price: 2527.50 SGD

Training Provider: SINGAPORE POLYTECHNIC

Course Reference: TGS-2024046244

S$2,528

About This Course

This is a module under the Specialist Diploma in Data Science (Data Engineering).

What You'll Learn

This module provides students with an understanding of Big Data technologies and the design and implementation of scalable data pipelines for processing large volumes of structured and unstructured data. Topics include the Hadoop ecosystem, Apache Spark, distributed data processing, Spark SQL, Spark MLlib, and Spark Streaming. Students will develop practical skills in building modern data pipelines, analysing large-scale datasets, and implementing machine learning and streaming analytics applications. The module also introduces Generative AI-assisted and agentic workflows to enhance productivity in data engineering tasks while maintaining emphasis on core technical competencies, responsible AI usage, and current industry practices.

Entry Requirements

Polytechnic Diploma/ University with Engineering or IT diploma/degree:
Applicants must have an Engineering/ IT diploma or degree from a recognized polytechnic*/ university** in Singapore

Polytechnic Diploma/ University with Maths requirement:
Applicants must have any other diploma or degree from a recognized polytechnic*/ university** in Singapore, and possess a Pass grade in either GCE ‘O’ level Mathematics or a Mathematics subject at diploma level.

Recognition of Prior Learning (RPL):
Applicants with relevant work experience in a data-related or analytical role will be considered on case-by-case basis, with consideration of 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.

* NYP, NP, RP, SP or TP
** NTU, NUS, SIT, SMU, SUSS or SUTD (Appl. with degrees from other universities are considered on a case-by-case)