Introduction to Data Science

Take your first step into the world of Data

Data science is receiving an increasing attention due to its research and application significance. This course provides a basic introduction to data science, consisting of data management, data visualization, data preparation, data analysis, data science modeling, and a brief description of advanced data science and artificial intelligence. The students can expect to learn basic knowledge of data science and how it can be applied to the real life.

Course Details

Course Dates:

27 February 2019

Sorry, registration is closed. Please try the next intake.

19 March 2019

Closing date: 26 Feb 2019

26 April 2019

Closing date: 5 Apr 2019

27 May 2019

Closing date: 6 May 2019

1 day, 9 am to 5 pm


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' levels Mathematics.

Programme Outline

Learning Objectives
  1. Data Management
  2. Data Visualisation
  3. Data Preparation
  4. Data Analytics
  5. Data Modeling
  6. Data Science Clustering
  7. Advanced Data Science and Artificial Intelligence
Part 1 - Data Management

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?
  • Who are the stakeholders?
  • Where does data come from?
  • How can I apply Data Science at work?
  • Steps to conduct Data Analytics
Part 2 - Data Visualisation

Data visualisation is beyond just graphs and charts. It's about communicating data in a visual, concise and meaningful manner to the relevant stakeholders. Good data visualisations should help decision makers to make faster and better decisions; they should be able to help these stakeholders identify trends better and understand difficult concepts in an easier way.

Part 3 - Data Preparation

Data comes in all shapes and sizes, they can be unstructured or structured and come from all venues. Data Wrangling helps with "cleaning" or mapping of the raw data into more meaning formats that can then be translated into more valuable analytics.

Part 4 - Data Analytics

Here comes the power of data. Participants will learn how to use Analytics to make sense out of data. Learning basic statistical techniques, hypothesis testing, and visualisation techniques, participants would be able to quickly and effectively interpret and communicate vital information derived from data to stakeholders. Participants will get a chance to learn basic usage of analytics and visualisation tools such as Power BI.

Part 5 - Data Modelling

Data modelling involves a deeper understanding of your organisation's data. It is how you manage data and the evaluation of how this is done in the organisation, whether the model has the right fit and relevance. Having learnt how to interpret data, one of the most exciting part of this programme is prediction. Predictive analytics can help organisations forecast resources effectively and improve processes.

Participants will learn Data Modelling techniques such as Regression, Correlation, Bayesian probability analysis, to develop models to based their prediction on.

Combined with the power of Machine Learning, participants will witness how they can train systems to "learn" patterns and perform tasks automatically, thereby enabling businesses to operate more efficiently.

Part 6 - Data Science Clustering

Diving deeper into Data Modelling is Clustering. Data Science Clustering is a "unsupervised" Machine Learning technique, which involves grouping of data. This method allows for grouping or profiling segments. In application for example, marketers can find it extremely useful to target particular customer segments based on similar attributes the data display.

Part 7 - Advanced Data Science and Artificial Intelligence

Artificial Intelligence (AI), the next frontier, combined with data science, AI has the ability to process more efficiently, make faster decisions, consider more than data than humans do. With the power of Machine Learning, the promise of automating tasks, providing insights and advise humans to make better decisions, AI is most definitely a field set to grow exponentially in tech and business.

Course Fees and Funding

Course Fee

Full Course Fee: $963 (Inclusive of Prevailing GST)
Course fee inclusive of
(1) Course materials
(2) Lunch and 2 x Light Refreshments

Funding: SkillsFuture Series

Full Course Fee


Less: Course fee grant (70%)


Nett Course fee


GST (7%) on Nett Course fee


Total Nett Course fee Payable inclusive GST


Further funding under Enhanced Training Support for SMEs ("ETSS")

Less: additional top-up 90% if eligible under ETSS


Nett Course fee under ETSS


GST (7%) on Nett Course fee


Total Nett Course fee Payable (ETSS + GST on Nett Course fee)


Further funding under SkillsFuture Mid-career Enhanced Subsidy ("MCES")

Less: additional top-up funding to 90% if eligible under MCES


Nett Course fee under MCES


GST (7%) on Nett Course fee


Total Nett Course fee Payable (MCES + GST on Nett Course fee)


Further funding under Workfare Training Support ("WTS")

Less: additional top-up funding to 95% if eligible under WTS


Nett Course fee under WTS


GST (7%) on Nett Course fee


Total Nett Course fee Payable (WTS + GST on Nett Course fee)



Dr Uwe Kaufmann Senior Fellow Managing Director at Centre for Organisational Effectiveness

Dr Kaufmann holds a PhD in Mechanical Engineering. He has more than twenty years of experience in implementing organisational improvements and changes in a wide range of industries. This includes private organisations such as Alstom, Aon, Armstrong, Bao Steel, Bosch, Bosch Siemens Home Appliances, Flextronics, Johnson & Johnson, JP Morgan, Schneider Electric, DB Schenker, Siemens, TCL, TRW, Wilmax Systems; as well as Public Service agencies such as ISCA, MSF, MFA, MinDef, MOF, MOH, MOM, MTI, IE Singapore, Muis and the Kingdom of Tonga.

You might also be interested in these courses:

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Introduction to HR Analytics

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

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 PDPA and Privacy Terms and Conditions

Personal Data Protection Act

SUTD collects, uses and discloses personal data in compliance with the Personal Data Protection Act.
Please contact the SUTD Personal Data Protection Officer at for the following matters:

  • Questions relating to SUTD’s collection, use or disclosure of your personal data

  • Giving/withdrawing consent to the collection, use or disclosure by SUTD of your personal data

  • Request for access to your personal data

  • Request for correction of your personal data

  • Giving/withdrawing consent to receive marketing messages from SUTD

  • Any other queries or feedback regarding SUTD’s policies and practices with respect to the protection of personal data.

Privacy Statements

  • SUTD collects, uses and discloses personal data to support its teaching, learning, research, administration, personal development and other functions of the University, in compliance with the Personal Data Protection Act.

  • If you are only browsing this website or using the Search function, we do not capture data that allows us to identify you individually. This site automatically receives and records information on our server logs from your browser, including your IP address, cookie information, and the page(s) requested. Although user sessions are tracked, the users remain anonymous.

  • If you choose to send an application or an e-mail that contains personally identifiable data, for us to process the application or to render you a service, we may share relevant data within SUTD, or if necessary, with Government agencies or universities, so as to serve you efficiently and effectively, unless such sharing is prohibited by legislation. We may also need to disclose personal data as required by law or a court order. We will not share your personal data with private entities, except where such entities have been authorised to carry out specific SUTD services.

  • For your convenience, when you are carrying out a transaction using your personally identifiable data, we may also display to you data you had previously supplied to us or to Government or private entities that have been authorised to carry out specific SUTD services). This will speed up the transaction and save you the trouble of repeating previous submissions. Should the data be out-of-date, please supply us the latest data. We will retain your personal data only as necessary for legal or business purposes.

  • To safeguard your personal data, all electronic storage and transmission of personal data are secured with appropriate security technologies.

  • This site may contain links to other independently-managed websites within the SUTD network and to some sites outside the "" domain whose data protection and privacy practices may be different from ours. We are not responsible for the content and privacy practices of these other websites and encourage you to examine the privacy notices of those sites.

  • Please keep in mind that whenever you voluntarily disclose personal data online – for example on message boards, through e-mails, or in chat areas – that information can be collected and used by others. By posting personal data online that is publicly accessible, you may receive unsolicited messages from other parties in return.

    Please contact the SUTD Personal Data Protection Officer at for the following matters:

  • Questions relating to SUTD’s collection, use or disclosure of your personal data

  • Giving/withdrawing consent to the collection, use or disclosure by SUTD of your personal data

  • Request for access to your personal data

  • Request for correction of your personal data

  • Giving/withdrawing consent to receive marketing messages from SUTD

SUTD Terms and Conditions

Methods of Payment

  1. Credit Card (Visa & MasterCard only) payment at SUTD campus One-Stop Centre

  2. Debit Card payment at SUTD campus One-Stop Centre

  3. Cheque make payable to “Singapore University of Technology and Design

  4. Invoice to Company (for Company Sponsored Participants)

  5. e-Invoice (for Ministries and Statutory Boards)

  6. Online Payment: DBS Internet Banking, DBS Mobile Banking & DBS Paylah!

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 Workfare Training Support ("WTS")

To qualify, individuals must meet the following criteria:

  1. Be a Singapore Citizen; and

  2. Aged 35 years and above (13 years and above for Persons With Disabilities); and

  3. Earn a monthly income of not more than $2,000.

  4. Training allowance is only available for individuals who pay for their own training.

  5. Individuals can apply at any of WSG's Careers Connect or NTUC's e2i centres up to 30 days (including weekends and public holidays) before or after the start of the course.

    For more info, please visit WSG 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