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Introduction to Data Science

Take your first step into the world of Data

Across the world, and industries, data science is in demand, and is receiving an increasing attention due to its research and application significance. Modern professionals are recognising the need to acquire skills in data science to stay relevant in the increasingly digital economy.

This introductory course provides a basic overview of data science which consists of data acquisition, data preparation, data analysis, data science modeling, and data visualisation. Participants can expect to learn the basic knowledge of data science and how data science can be applied in real life.

To go deeper into Data Science, you may wish to consider the ModularMaster in Data Science which covers a myriad of specialised topics in Data Science.

Course Details

Course Dates:
No dates available currently.

Past Intakes

  • Intake 17: 24 and 25 August 2020
  • Intake 16: 3 and 6 July 2020
  • Intake 15: 19 March 2020


  • 1 day (In-class)

Who Should Attend

Adult learners with some computer knowledge and a keen interest in data.

Elementary learners or novices who want to learn how data can be applied at work.


  • Preferably with O-level Mathematics
  • Basic familiarity with Microsoft Excel and PowerPoint

Programme Outline

Learning Objectives
  1. Data Management
  2. Business Case and Data Acquisition
  3. Data Preparation
  4. Data Analytics
  5. Data Modelling
  6. Data Visualisation
  7. Decision Making
Part 1 - Data Science and Business Case Study

This segment deals with the why and what to get participants up to speed with common terms used in Data Science and aims to answer:

  • What is Data Science exactly?
  • Steps in a typical Data Science lifecycle
  • Who are the stakeholders?
  • Where does data come from?
  • How can one create a Data Dictionary from a common tool like spreadsheet?
  • How can I apply Data Science at work?

Clearly stating the Business Case and the objectives for the Data Science task is a prerequisite for efficient and effective data analytics. It serves to avoid unnecessary work and frustration during data acquisition and during consecutive steps. The Business Case drives the selection of appropriate data acquisition methods and sources. This also helps to keep Data Preparation, Data Analysis, Data Science Modelling and Algorithm and Data Visualisation in scope.

Part 2 - Data Acquisition

The art of acquiring data have never been so important than before, in particular when big data sets in the new paradigm for data-centric business. From multi-channel data acquisition to defining various sources of data such as commercial or public or even governmental dataset, never have we faced such an explosive growth of data, yet we have not been able to potentially set foot onto a new planet full of data that is untapped. Businesses with the inclination towards a data-first approach as part of their drive towards efficiency would definitely help them to envision a new way of conducting their traditional business whether is capitalising on public tweets from social media to understand the consumer trend or the amalgamation of various types of data such as structured and unstructured data.

Part 3 - Data Preparation

Data comes in all shapes and sizes, it can be unstructured or structured. Data pre-processing helps to format the existing data set from a raw form into a more interpret-able form of data set consumable for Data Analysis and Algorithm.

Part 4 - Data Analytics

Data analytics is the core of Data Science. Participants will understand the involvement of Analytics in Data Science. By understanding the science of analysing raw data to make well-informed choices around the meaningful information, it can help professionals and aide front-liners in understanding how their roles can make an upstream impact in within the Data Science pipeline, even when they are not directly part of the Data Analytics team. Participants will learn Data Analysis and Visualisation with Excel.

Part 5 - Concepts of Machine Learning and Algorithms

Participants will appreciate the role of Machine Learning and Algorithms within a mature organisation which capitalize on the strengths of Machine Learning. Participants will learn simple Data Science Modelling and Algorithm such as Simple Linear Regression in Excel only.

Part 6 - Data Visualisation

Data visualisation is beyond just graphs and charts. It's about communicating data in a visual, concise and meaningful manner to stakeholders. Good data visualisations should help them draw conclusions faster and more solid. Participants will learn how to apply data visualisation with Excel.

Part 7 - Decision Making

Data Analysis and Data Science Modelling and Algorithm as well as the visual presentation of these results are the basis for decision making. Translating these results and visuals into business language and using it for data storytelling are vital tasks for every Data Scientist. After that, stakeholders are able to make data-driven decisions easily and confidently.


Participants to complete a simple assessment to evaluate course understanding and augment learning outcomes.

Course Fees and Funding

SkillsFuture Course Fee Subsidy

Fee after subsidy

GST on Fee after SSG Course Fee Subsidy

You pay

Mid-career Enhanced Subsidy (MCES)

Fee after subsidy

GST on Fee after SSG Course Fee Subsidy

You pay

Enhanced Training Support for SMEs (ETSS)

Fee after subsidy

GST on Fee after SSG Course Fee Subsidy

You pay

Full Course Fee (without subsidies): $963 (inclusive of prevailing GST)


Johnson Ang
Instructor, SUTD Academy

Johnson Ang has a Masters in IT Analytics from SMU and is certified and a member of CQF, ACTA and CEH. He previously work as a Data Scientist with MND and was an ex-affiliate University lecturer for Cardiff Metropolitan UK University and ex-lecturer with EASB in 2018 and was also Corporate and Open-Run trainer for 2 years.

His experience spans more than 10 years of working experience, of which 4 years of experience in the Banking Wide Operations and has been particularly involved in IT Analytics banking projects within the Risk Management and Financial Instrument sphere, and 4 years in the Real Estate, FMCG, Construction and Education Sector. He is familiar with typical banking software and acquainted with popular tools such as SAS, JMP, Oracle, VBA, Access, Python, R, Tableau, Weka, C and Java. He also has working knowledge in the area of Data Science; Analytics, Machine Learning and Deep Learning.

You might also be interested in these courses:

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Foundation of Data Science

Choose to go deeper into Data Science with this programme and earn 12 subject credits.

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Introduction to AI

Discover the Power of AI and learn how you can make use of AI to make better decisions for your business.

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Introduction to HR Analytics

See how analytics can be applied into the various HR functions.



Policies and Financing Options

SSG Funding Terms and Conditions

Use of Personal Details

In consideration of the subsidy provided by SkillsFuture Singapore Agency (“SSG”) through the SUTD Academy for the Course,

I consent to:

The collection, use and disclosure to relevant third parties of my personal data by the SUTD Academy including but not limited to personal particulars, attendance records, assessment/performance records, for the following purposes:

  1. Reporting of national statistics and conducting of holistic continuing education training research and analysis;

  2. Facilitate the conduct of the relevant surveys and audits in relation to the Course;

  3. General administration of the Course including but not limited to processing of the subsidy provided by SSG;

  4. Publicity and marketing of the Course or other Courses to be provided by SSG or SUTD Academy; and

  5. SSG or its Appointed Auditors or Nominated Representatives to directly contact Course Participant to obtain information deemed necessary for the purposes of conducting effectiveness survey or audits in relation to the Course.

I agree to:

  1. Attend and complete all lectures, class exercises, workshops and assessments;

  2. Complete the Course feedback at the end of the Course;

  3. Complete the post Course survey sent about 3 to 6 months after class attendance; and

  4. Sign up for a personal email account.

SUTD Privacy Statement

For more information on SUTD's privacy statement, please visit

SUTD Terms and Conditions

Methods of Payment

Learn more about the available payment modes.

Cancellation & Refund Policy

  1. If a written notification is sent to within 24 hours after course registration deadline there will be no cancellation charges. A full refund will be made. 

  2. No refund is provided if written notification is more than 24 hours after course registration deadline. SUTD Academy reserves the rights to collect the full fee amount from the participant.

Replacement Policy

Companies may replace participants who have signed up for the course by giving a 3-working day notice before the course commencement date to Terms and conditions apply.

Registration Policy

  1. Course may be cancelled due to insufficient participants. SUTD Academy will not be responsible or liable in any way for any claims, damages, losses, expenses, costs or liabilities whatsoever (including, without limitation, any direct or indirect damages for loss of profits, business interruption or loss of information) resulting or arising directly or indirectly from any course cancellation.

  2. Course enrolment is based on a first-come, first-served basis.

  3. SUTD Academy reserves the right to change or cancel any course or instructor due to unforeseen circumstances. 

Types of Funding

Funding under Mid-Career Enhanced Subsidy ("MCES")

  1. MCES is an enhanced Subsidy to encourage mid-career individuals to upskill and reskill, thereby helping them to remain competitive and resilient in the job market. With this, all Singaporeans aged 40 and above will receive higher subsidies of up to 90% course fee subsidy for SSG-funded certifiable courses.

  2. Individuals/employers are not required to submit an application for the MCES. Those pursuing SSG-funded programmes will be charged the appropriate subsidised fees by SUTD Academy if they are eligible MCES. Individuals/employers will only need to pay the nett fee (full course fee after SSG's grant).

    For more info, please visit  SkillsFuture website at

Funding under Enhanced Training Support for SMEs ("ETSS")

  1. ETSS is an enhanced funding to enable SMEs to send their employees for training.

  2. SMEs will enjoy subsidies of up to 90% of the course fees when they sponsor their employees for SSG-funded certifiable courses.

  3. In addition to higher course fee funding, SMEs can also claim absentee payroll funding of 80% of basic hourly salary at a higher cap of $7.50 per hour. SMEs may apply for the absentee payroll via the SkillsConnect system.

  4. To qualify, SMEs must meet all of the following criteria:
    - Organisation must be registered or incorporated in Singapore
    - At least 30% local shareholding by Singapore Citizens or Singapore Permanent Residents
    - Employment size of not more than 200 (at group level) or with annual sales turnover (at group level) of not more than $100 million
    - Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
    - Trainees must be Singapore Citizens or Singapore Permanent Residents

    For more info, please visit SSG website at

Funding under Union Training Assistance Programme ("UTAP")

UTAP is a training benefit for NTUC members to defray their cost of training. This benefit is to encourage more union members to go for skills upgrading.

NTUC members enjoy 50% unfunded course fee support for up to $250 each year when you sign up for courses supported under UTAP (Union Training Assistance Programme).

For more info, please visit NTUC's website.