WSQ – Data Analytics at Work (SF) (Synchronous and Asynchronous -e-learning)

The Data Analytics at Work course aims to equip learners with the knowledge and skills in data preparation and extraction, transformation, and loading (ETL) data from different sources and combine them into a single dataset. Learners will be equipped to perform data analytics workflows, interpret graphs and charts, apply time series analytics, use text mining analytics, review image analytics, and familiarize themselves with the major types of analytics.

WSQ – Data Analytics at Work (SF) (Synchronous and Asynchronous -e-learning)

Key Facts 

  • Course duration: Please refer to the details below

  • Intake dates: Start in April, June, July, August, September, October, November, or December

  • Total training fee: S$1,950

  • Funding: Up to 90% of funding is available. Please see the criteria below
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This course is specifically designed to develop learners' professional skills and capabilities in designing and conducting data studies to drive organisational decisions and insights. It aims to equip learners with skills to conduct organisational data collection, preparation, analysis, and data analytics capability by improving business performance criteria and data design for organizational processes. Learners will be able to uncover actionable comprehensions from data and identify opportunities within their respective departments or organisation where data can be influenced. The Synchronous and Asynchronous mode, as well as face-to-face strategies, will provide learners to be able to on time-based practical assignments, quizzes, and forums for discussions.

 

Please choose one of the following options:

1

4.5 days, 9 AM - 6 PM (Monday - Friday). 9 hours/day *4 days + 3 hours of Assessment.

2

2 weekends (Saturday and Sunday) + 3 hours of Assessment. 

3

14.5 days - 2 weeks, 7 PM - 10 PM (Monday - Friday). 

4

Customized upon corporate request. 

5

3 months, 1 session/week, 3 hours/session.

At the end of the course, learners will be able to:

1) Interpret the data patterns in business cases and benefits of business acumen.

2) Select relevant methods to appraise solutions and provide insights.

3) Select appropriate methods to interpret patterns in data and manage data science projects.

4) Prioritise data science projects to implement data models to examine business assumptions.

5) Manage organisational capacity, business problems and provide insights for the functional projects.

6) Run complex data mining models to provide insights in accordance with the standard procedures.

7) Communicate the results of data science projects using methods to explore a data set visually and analytically.

8) Apply relevant methods, tools and techniques to manage the capacity to perform data science projects. 

9) Make recommendations to guide organizational decision-making and use methods to measure the performance of the data science team.

 

The assumed skills and knowledge for this course are as follows:

  • Aged between 21 years old or above;
  • Minimum must have ONE GCE “O” Level;
  • Able to read, listen and speak English at a proficiency level equivalent to Employability Skills System (ESS) Literacy Level 6;
  • Able to count with a proficiency equivalent to Employability Skills System (ESS) Numeracy Level 6;
  • Have basic computer literacy (Workplace Skills Series - Information & Communication Technologies Skills).

Learners may be required to submit the relevant documents conforming to the pre-requisites for the course as stated above where necessary, if they do not meet the pre-requisites.

If the learner does not meet the entry requirement, the learner would be rejected from the course.

This accreditation enables Singaporeans and Singapore PR holders to get a part of their course funded by the SSG. Subjected to the eligibility and funding caps, the funding support is up to 90% for Singaporeans and up to 80% for Singapore PR holders.

Course Fee Funding for Self-sponsored Individuals (as of 30 Apr 2021)

Certifiable courses approved by SSG Course level Courses starting before 1 Jan 2022 Courses starting on or after 1 Jan 2022
Singapore Citizens (SCs) and Permanent Residents (PRs) (Self-sponsored individuals must be at least 21 years old) PMET Up to 50% of course fees, capped at $15 per hour Up to 50% of course fees
Non-PMET Up to 80% of course fees, capped at $17 per hour
SCs aged ≥ 40 years old (SkillsFuture Mid-career Enhanced Subsidy) PMET Up to 90% of course fees, capped at $50 per hour Up to 70% of course fees
Non-PMET Up to 90% of course fees, capped at $25 per hour

To receive funding from SSG, you must meet the following criteria:

  • Pass the course
  • Achieve a minimum of 75% of the attendance
  • Must not be barred from receiving government grants

  • You may also be eligible for the course fee (CF) funding at the current rates offered by SkillsFuture Singapore (SSG). For more details, please refer to this page.
  • Individuals aged 40 and above may also be eligible for the SkillsFuture Mid-Career Enhanced Subsidy (MCES). For more details, please refer to this page.
  • Singaporeans may also use their SkillsFuture credit to offset course fees payable. For more details, please refer to this page.

Modules

Explain data collection, data preparation, exploration and modelling, evaluation and interpretation, data transformation. Use disciplines that support data analytics. Analyse what to avoid when building a model.

Import data and explore data. Use the steps for cleaning and transforming data by simplifying repetitive data preparation tasks. Create and share datasets using relevant techniques.

Explain the process for scaling and delivering data output. Illustrate the steps of Sub-setting and filtering data. Analyse the application for merging data sources.

Request More Information

Contact a programme advisor by calling
+65 6580 7700

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