University of Malaysia Pahang UMP

University of Malaysia Pahang UMP

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Bachelor of Applied Science (Honours) Data Analytics

  Study Mode FULL TIME
  Duration 4 years
Intake Deadline
  Tution Fees N/A

The Bachelor of Applied Science (Honours) Data Analytics programme is developed in line with UMP's vision, mission and educational goals to be a distinguished Technological University. The three and half year programme is designed to produce highly skilled and competent graduates in the field of Data Science who are capable to gain insights of the data and make effective decisions using Data Science and Analytics skills. Data Science is a new exponentially growing field that consists of a set of tools and techniques, and requires an integrated skill set from statistics, mathematics, computer science and the use of current technology in computer software or programming language. The Data Science elements are part of the main pillars of the Fourth Industrial Revolution (4IR).  The Industrial Revolution gives birth to new emerging technologies which includes automation, digitilasation and artificial intelligence that bring forward new challenges in data science with the discovery of information from large volumes of data. 

This new industry-relevant curriculum comprises of 120 total credit hours, which includes University Courses, Faculty Courses, Core Programme Courses, Elective Courses, Data Science Projects and one year of industrial Training/Internship. Students will undergo Work-Based Learning in selected industry through Block Release structure in Semester 6 and 7 after they have completed all the courses from semester 1 to 5. Students will learn the architecture of Data Science and Analytics system through seven core areas of competencies including; (i) Mathematical Skills (ii) Programming Skills, (iii), Data Preparation and Data Visualization Skills, (iv) Statistical Modelling Skills, (v) Machine learning Algorithms Skills, (vi) Advanced Analytical Skills (vii) Managerial Skills, and (viii) Research and Practical Skills. Students will be equipped with an in-depth knowledge of Data Science and Analytics to become an expert analyst who will use the latest data management and analytics tools. They will learn how to apply this expertise in the real world through final year project and internship program in any related industry in order to prepare for an exciting career ahead.

Data science is a highly innovative area of knowledge. The profession was described as the "Sexiest Job of the 21st Century," by Harvard Business Review in October 2012.  Data Science degree graduates from UMP are expected to build a career as data science professionals in various sectors and industries. Data-centric industries such as business services, information technology, banking and telecommunications are currently leading the data science recruitment in Malaysia.  This programme focuses on two of the key role of data science teams in career development which is data analyst and data scientist.  Data analyst plays an important role in deriving value and seeking patterns from data to assist organisations in the development of their predictive capabilities. Data scientist will use analytical techniques combined with data skills to develop scalable and robust analytical models. Data scientists’ skills are highly valued across all fields within the private sector, government and non-profit organisations.  Hence, Data Science and Analytics knowledge and tools are vital for the sustainability of science and technology advancement. 

For this program, Faculty of Industrial Sciences & Technology (FIST), Universiti Malaysia Pahang (UMP) has approached 21 companies from various industries which has potential to be appointed as the 2u2i Strategic Industry Partner. The Strategic Industry Partner will accept the students of Bachelor of Applied Science (Honours) Data Science to experience Work Based Learning (WBL) at their company. 


 PEO1 Employable graduates with the knowledge and competency in Occupational Safety and Health
 PEO2 Graduate having professional attitude in fulfilling their role in Occupational Safety and Health
 PEO3 Graduate engage in lifelong learning activity in their organization


No MQF Program Learning Outcome
PO1   Describe, interpret and apply knowledge of science and engineering in OSH
PO2   Assess and analyze issue of OSH in workplace and community
PO3   Identify and analyse critically OSH problems to provide solutions based on evidence
PO4   Interpret, analyze, synthesis and recommended preventive and corrective measures
PO5   Apply evidence based scientific principles in discussing ideas of improvement in OSH
PO6   Demonstrate leadership, and team working skills
PO7   Communicate effectively in verbal and written forms
PO8   Collaborate with other OSH professionals
PO9   Adhere to the legal, ethical principles and the professional codes in OSH
PO10   Apply broad business and real world perspectives code of conduct in OSH
PO11   Demonstrate sensitivities and responsibilities towards community, religion and env
PO12   Apply skills and principles of lifelong learning in academic and career development


Year 1
  •  Discrete Mathematical Structure
  •  Linear Algebra
  •  Problem Solving
  •  Intoduction to Data Science
  •  Counting and Probability
  •  Differential Equation
  •  Programming Technique
  •  Storytelling and Data Visualisation
  •  Applied Statistics
  •  Principles of Operation Management

Year 2
  •  Applied Calculus
  •  Data Structure and Algorithm
  •  Database System
  •  Data Science Programming I
  •  Mathematical Statistics
  •  Data Science Programming II
  •  Data Wrangling
  •  Data Warehousing
  •  Artificial Intelligence
  •  Industry Quality Management
  •  Research Methodology

Year 3
  •  Operational Research
  •  Experimental Design Analysis
  •  Statistical Modelling and Simulation
  •  Machine Learning
  •  Data Mining
  •  Data Science Project I

Year 4
  •  Elective I
  •  Elective II
  •  Elective III
  •  Data Science Project II

 Year 5
  •  Industrial Training


  • Data Analyst (Penganalisa Data)
  • Statistician (Ahli Statistik/Perangkawan)
  • Data Scientist (Saintis Data)
  • Data Technopreneur (Usahawan Data)
  • Digital Data Analyst (Penganalisa Data Digital)
  • Programmer (Pengaturcara Komputer)
  • Business and Marketing Analyst (Penganalisa Perniagaan dan Pemasaran)

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