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Course Detail

CZ4032 Data Analytics and Mining
Objectives
This subject covers a comprehensive introduction to data analytics and mining. Introduction of Data Analytics & Mining; Data Pre-processing; Data Analytics & Visualization; Cluster Pattern Analysis; Predictive Pattern Mining; Association Rule Mining; Anomaly Detection.
Outline
a) Understand the multidisciplinary nature of data analytics, data mining and knowledge discovery
b) Become familiar with some basics and current research issues in data mining
c) Acquire hands-on experience in using conventional data mining software/tools
d) Ability to critically evaluate original research papers
e) Ability to communicate complex technical material orally and in written form
f) Ability to learn independently by continuous interactions with a set of self-learning modules that complement the physical contact hours
Who Should Attend
Working professionals with prior knowledge of CZ2001 Algorithms previously.

Eligibility Criteria
At least 21 years of age
Have 2 years of full-time work experience, or have fully discharged full-time NS liability, or are currently employed on a full-time basis.
Degree in Engineering/Science or
Polytechnic Diploma with relevant working experience
Details
Date(s): 12 Aug 2019 to 06 Dec 2019
Time: Refer to Class and Exam Schedules
Venue: ONE-NORTH
Closing Date of Registration: 18 Nov 2018
Course Fee Payable:(Inclusive of GST) Refer to the course fee table

Subsidy/Funding
MOE (SBMC) No
E2I No
SSG Yes
Academic Units (AU)
Number of AU: 3
Online Registration
Closed
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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.
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