Specialist Diploma in Data Analytics

Offered by School of InfoComm Technology

Post-Diploma / 1 year / TGS-2021002414

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Course Information
Learning Outcomes
Course Schedule
Lesson Plan
Certification
Entry Requirements
Course Fees
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Course Information

Big data is growing at an incredible speed, and the capacity to make sense of it to make informed decisions has become a vital part of the way industries operate. Analytics is used everywhere from the health industry to aviation, which means having the skills to work with data has now become a valuable commodity.

 Click on this link* to view our webinar (recording) to learn more about our programme and get your questions answered about this course.
*Submit your request to view our recording.

Good news! Module exemptions are now available for successful applicants to this course through a challenge exam starting with the Oct 2023 Intake.  Selected modules is:

  • Data Visualisation and Storytelling

More details about the challenge exam will be available in your admission package. The challenge exams will be conducted on campus on 15 Sep 2023.  Have questions on the challenge exams? Email EnquiryPTD@np.edu.sg.

Learning Outcomes

Begin the learning journey into data analytics by picking up critical technical skills and essential domain knowledge.

Learn to derive actionable insights that help drive business value through hands-on data analysis approaches. Plus, acquire fundamental coding abilities to effectively perform data visualisation, data exploration, data wrangling and statistical analysis. Build a strong technical foundation before progressing to advanced data analytics techniques.

Course 
Schedule

Course Date: 16 Oct 2023 – Oct 2024
Application Period: 17 Jul – 31 Aug 2023
Application Outcome Date: One week after application closes

Day: Mon and Thu
Time: 6pm to 10.30pm
Delivery Mode: Face-to-face & Home-based Learning (Sync)
Venue: Ngee Ann Polytechnic/Online

Ngee Ann Polytechnic reserves the right to reschedule/cancel any programme, modify the fees and amend information without prior notice.

Lesson Plan

Post-Diploma Certificate in Data Visualisation and Programming for Analytics (TGS-2021002415)
Module
Data Visualisation and Storytelling (TGS-2023020444)
This module discusses the principles and techniques for creating effective visualisations based on graphic design and perceptual psychology. Using widely adopted tools, you will apply these principles and techniques to create rich visualisations for analysis and presentation. You will learn visual analysis techniques to grasp pertinent information, as well as apply exploratory techniques to further derive key insights. Data storytelling and information graphics best practices will also be explored to allow learners to present data effectively and eloquently.
Module
Programming for Analytics (TGS-2023020443)
The aim of this module is to equip you with sufficient mastery of a programming language to perform operations and analysis. This module is suitable for learners with little or no programming background. The programming language taught is Python, which is fast becoming the world's most popular coding language due to its simplicity and flexibility. Its popularity also stems largely due to its wide range of applications in areas such as machine learning, network automation, and internet of things. The module highlights the syntactical and algorithmic aspect of programming to participants. You will be able to code using Python, from basic to complex algorithms progressively.
Post-Diploma Certificate in Data Wrangling and Descriptive Analytics (TGS-2021002416)
Module
Data Wrangling (TGS-2023020446)
The aim of this module is to equip you with the tools and skills sets to handle, clean and prepare large curated data sets for data analytics purposes. Participants of this module should minimally have basic programming knowledge and be able to understand and decipher simple syntaxes. The processed data sets will allow for meaningful statistical analysis, data modelling, and machine learning to be easily performed. Emphasis will be placed on the Extraction, Transformation, and Loading (ETL) of data sets. The use of relevant programming libraries for Missing and Time Series Data will also be explored. Learners will experience the process of exploratory data analysis, normalization of data and data distribution, which will be crucial for subsequent understanding of machine learning concepts and models.
Module
Descriptive Analytics (TGS-2023020445)
In this module, you will first be exposed to Descriptive Statistics concepts, delving into topics such as central tendency, normal distribution, measures of variability, variance and standard deviation. Following which you will be able to perform univariate, multivariate and correlation analysis in order to identify inherent patterns and derive key insights from business data. You will also create appropriate visualisation components using systems to gain insights from the data. These visualisation components will be synthesized into dashboards that can be readily adopted by users.

Certification

1 Specialist Diploma
2 Post-Diploma Certificates
4 Modules

Certification

You are required to complete 2 post-diploma certificates within 2-year validity period to be awarded the Specialist Diploma qualification.


Entry Requirements

Applicants with any of the following qualifications are invited to apply for the course:
  • You will need to have a local Polytechnic Diploma or recognized Degree (with English as the medium of instruction) in business, engineering, technology, or any other disciplines with at least one (1) year of relevant work experience.
  • You are required to have working knowledge of Microsoft Office e.g. Word, Excel and PowerPoint. Students enrolled into the course are expected to bring along their personal laptop. Only Windows notebook computer (Microsoft Windows 10 or newer) is recommended as you will be using Windows-based software that is not compatible with the Apple Mac Operating System platform.

Course Fees

Funding period for this course is from 1 Apr 2021 to 30 Mar 2024.

Note:

  • The fees below are per semester. For full course fees throughout the semesters, refer here.
  • The fees below are inclusive of GST. Please note that the GST rate will be revised to 8% with effect from 1 Jan 2023, as such any payable course fees will be subjected to the new GST rate adjustments in 2023. Please refer to our FAQs for more information.
  • The fees below are determined based on prevailing funding policies and subject to review and revision.

SkillsFuture Credit
This course is eligible for SkillsFuture Credit.

All Singaporeans aged 25 years and above can use their $500 SkillsFuture Credit from the government to pay f​or a wide range of courses. The credits can be used on top of existing course fee subsidies/funding. This is only applicable for self-sponsored applicants and must be applied via the SkillsFuture Portal. More details on the SkillsFuture Credit Claims will be advised upon admission into the course. Find out more about SkillsFuture Credit here.

Union Training Assistance Programme (UTAP)
NTUC members enjoy 50% unfunded course fee support for up to $250 each year (or up to $500 for NTUC members aged 40 years old and above) when you sign up for courses supported under UTAP (Union Training Assistance Programme). Please visit e2i’s website to find out more.

Skills-Based Modular Courses (SBMCs) are bite-sized part-time courses for individuals to acquire new skills or deepen relevant skills, without the need to pursue a full diploma.  Refer here for course fees for SBMCs.

Applicants / Eligibility Fees
Singapore Citizens aged below 40 $556.14
Singapore Citizens aged 40 & above $370.76
Singapore Citizens sponsored by SME $382.88
Singapore PRs $1522.80
Singapore PRs sponsored by SME $394.80
Full course fee for SC (for repeat, deferred modules) $3707.56
Full course fee (for repeat, deferred modules)$3807.00