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EasyUni Sdn Bhd

Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
4.4

(43) Google reviews

+60142521561

EasyUni Sdn Bhd

Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
4.4

(43) Google reviews

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Prof Doc Data Science

Course overview

Statistics
Qualification Doctoral Degree (PhD)
Study mode Full-time, Part-time
Duration 3 years
Intakes September
Tuition (Local students) RM 135,535
Tuition (Foreign students) RM 198,220
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Admissions

Intakes

Fees

Tuition

RM 135,535
Local students
RM 198,220
Foreign students

Estimated cost as reported by the Institution.

Application

Data not available
Local students
Data not available
Foreign students

Student Visa

Data not available
Foreign students

Every effort has been made to ensure that information contained in this website is correct. Changes to any aspects of the programmes may be made from time to time due to unforeseeable circumstances beyond our control and the Institution and EasyUni reserve the right to make amendments to any information contained in this website without prior notice. The Institution and EasyUni accept no liability for any loss or damage arising from any use or misuse of or reliance on any information contained in this website.

Entry Requirements

  • Relevant qualifications accepted/recognised by the university.

Curriculum

Our Doctoral Research course focuses on pure or applied aspects of Data Science, with each student studying data from within their main discipline or area of employment. You will learn reflective and analytic approaches to data while engaging in your own data research.

The taught elements of the course include Data Ecology, Research Methods for Technologists, Applied Research Tools and Techniques, Spatial Data Analysis, Advanced Decision Making, Work-based Project Reviews and Planning for Doctoral Research.

These elements will be reinforced by the specialist knowledge of our course leaders, whose fields of expertise includes data cleansing, data integration, data mining, spatial analysis and predictive analytics.

Their recent research has engaged them in data from crime statistics, natural hazards, public health and business, keeping them at the forefront of new developments in the field.

Our cross-disciplinary approach to the subject means that whatever your area of interest, our researchers will have the experience and expertise to enhance your knowledge and skills.

The taught modules on this course are available to be taken as credit-bearing short courses by suitably qualified individuals.

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