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Course Detail

BS0004 Introduction to Data Science
This course aims to introduce you to the field of data science. By the end of this course, you should appreciate how data science contributes towards Singapore’s Smart Nation aspirations, potential ethical issues (especially with the use of AI), and its uses in the biological sciences. It is particularly noteworthy that biology is becoming increasingly digitized thanks to advancements in -omics platforms, advanced analytics, the advent of AI and cloud-based mega-data repositories. Hence, the modern biologist needs to understand how data science could potentially make his/her research more effective. You will learn what this exciting new field is about: how it relates towards Singapore, ethical issues and its application in biological sciences. You will also learn about some of the main themes related to data science, namely algorithms, AI and machine learning, logic, databases and networks.
a) Data science in the Singapore landscape
b) Socio-ethical implications of data science (and AI)
c) The qualities and skillsets required of a data scientist
d) The relevance of data science in biology
e) The importance of graphs in communication
f) Research design considerations and confounders
g) How data is organized using databases
h) How Logic helps clarify thinking process
i) Network theory and network biology
j) Machine learning evaluation metrics
k) Examples of machine learning algorithms
Who Should Attend
Data Scientist or Reasearchers working in academia and the local biotech industry
Eligibility Criteria
Diploma/Degree in Biological Sciences and equivalent with years related working experience.
Date(s): 09 Aug 2021 to 03 Dec 2021
Time: Refer to Class and Exam Schedules
Venue: LHN-TR+14
Closing Date of Registration: 15 Nov 2020
Course Fee Payable:(Inclusive of GST) Refer to the course fee table

E2I No
Academic Units (AU)
Number of AU: 3
Online Registration
Method of Payment
  1. Online Credit/Debit Card Payment (VISA and Mastercard only)
  2. Cash/Cheque/NETS payment at One-Stop@SAC (NTU Main Campus)
Withdrawal & Refund Policy

Once payment is made, applicant is committed to the completion of course. Course fee refunds will not be considered.

Terms and Conditions
  1. Course is subject to a minimum participation number before commencement.
  2. Course is subject to a first-come-first-serve basis.
  3. Registration is non-transferable.
  4. Student must meet all eligibility criteria for admission.
  5. Student is required to complete all assessments for each course.
  6. PaCE@NTU​ reserves the right to change or cancel any course or lecturer due to unforeseen circumstances.
  7. All details are correct at time of dissemination.
Privacy Clauses
At PaCE@NTU, participants’ personal information is collected, used and disclosed for the following purposes:
  1. To process your application.
  2. For course administration and billing.
  3. To enable the trainers to know the background of the course participants.
  4. To submit to organisations for course funding verification (only applicable to funded courses).
  5. To issue certificate to the course participants.
  6. For marketing of courses to participants via E-newsletter.
  7. To understand and study the profile of its course participants for NTU’s policy making and planning.
  8. To deal with any matter related to the course.
Full Data Protection and Privacy Statement : CLICK HERE
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