Master of Data Science - CS779

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Programme Profile

Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured. The Master of Data Science program aims to produce data professionals who are passionate about drawing meaningful insights from data using data science approach. The program is designed to provide you good analytical and programming skills to use data science from data storage, data analytics to practical applications with the aim of improving business or organization performance.

Programme Objective

  • To produce knowledgeable and technically competent data professionals who can lead in the field of data science.
  • To produce dynamic scholars who have critical thinking skills, able to innovate and develop new research ideas and solutions, and can contribute to society and nation technological advancement.

Admission Requirement

For bumiputeras students :

A Bachelor’s Degree  (level 6,Malaysian Qualification Framework, MQF) or its equivalent in the field of science, computer science, engineering, mathematics, statistics, business or economics or other related discipline from Universiti Teknologi MARA OR other local or foreign universities recognized by the Malaysian Government  with a minimum CGPA of 2.75 or equivalent;

OR

A Bachelor’s Degree (level 6, MQF) or its equivalent,  in the field of science, computer science, engineering, mathematics, statistics, business or economics or other related discipline with a minimum  CGPA of 2.50 and not meeting CGPA of 2.75, can be accepted subject to rigorous internal assessment process;

OR

A Bachelor’s Degree (level 6, MQF) or its equivalent,  in the field of science, computer science, engineering, mathematics, statistics, business or economics or other related discipline with  CGPA less than 2.50, with a minimum of 5 years working experience in  a relevant field may be accepted.

For international students :

  • TOEFL550 (PAPER BASED)
  • 213 (COMPUTER BASED)
  • 70-80 (IBT)

    OR

  • IELTS with at least band 6

Mode & Duration

  • Full Time: (3 - 4 semesters / 1½ - 2 years)
  • Part Time: (4 - 8 semesters / 2 - 4 years)

Plan of Study

Semester 1 Year 1
Enterprise Data Analytics, Advanced Data Organization, Statistical Computing, Research Methodology

Semester 2 Year 2
Advanced Data Science Technology , Statistical Data Mining, Advanced Decision Support System, Seminar and Industry Engagement, Elective I

Semester 3 Year 2
Data Science Project, Elective II, Elective III

Elective Courses

Business
Customer Analytics, Operations Analytics, People Analytics

Computing
Optimization with Natured Inspired Computing, Data Visualization, Text Analytics

Geo-spatial
Advanced GIS, Geo-spatial  Analysis and Modelling, Geo-visualization

Statistics
Time-series modelling and Forecasting, Applied Statistical Modelling, Applied Multivariate Analysis

Programme Structure

CORE COURSES

24 credit hours

PROJECT

9 credit hours

ELECTIVE COURSES

9 credit hours

Total

42 credit hours

 

Career Opportunities

Graduates of this master degree are able to fill job designations such as: Data Engineer, Data Analyst, Data Modeler, Business Analyst, Data Scientist, Public Health Analyst, Operations Manager, Systems Analyst, Market Analyst, Intelligent Systems Engineer and Business Development Manager. 

The graduates will have job opportunities in various sectors: business, finance, manufacturing, transportation, banking, insurance, telco, retail, medical and  oil & gas industries.