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Course Detail

CZ4071 Network Science
This course covers a number of topics in network science and its applications. The specific topics include network metrics, properties, and models, network querying and analytics, network dynamics, and distributed graph engines. Students will Learn advanced network science principles relevant to drive data science in the 21st century. Apply network science principles to implement a real-world complex network application.

In addition to learning about network science, this course will also give the students an opportunity to practice important research skills. Students will gain experience reading and critically evaluating original research papers. Practice communicating complex technical material, both orally and in written form.
a) Understand the importance of, and uses for, network science in the 21st century
b) Understand various metrics used for network analysis
c) Understand real-world properties of massive networks
d) Understanding of how a variety of queries are evaluated on massive networks.
e) Understand various analytics techniques available for massive networks.
f) Understand the architecture of existing distributed graph engines and their role in network science
g) Acquire the understanding of the role of network science in solving major problems in a variety of domains such as social, biological, transportation, and cyber security.
h) Ability to critically evaluate original research papers.
i) Ability to communicate complex technical material orally and in written form
j) Develop ability to learn independently by continuous interaction with a set of self-learning modules that complement the physical contact hours
Who Should Attend
Working professionals with prior knowledge of:

Pre-requisite: CZ2002 Object Oriented Design and Programming
Eligibility Criteria
Participants who have completed the Specialist Certificate in Software Basics II OR relevant Bachelor degree holder and Polytechnics Diploma with relevant work experiences.
Date(s): 11 Jan 2021 to 07 May 2021
Time: Refer to Class and Exam Schedules
Venue: LT4
Closing Date of Registration: 30 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.
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  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.
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