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Students
مصاريف
تاريخ البدء
وسيلة الدراسة
داخل الحرم الجامعي
مدة
3 years
حقائق البرنامج
تفاصيل البرنامج
درجة
درجة الدكتوراه
تخصص رئيسي
Artificial Intelligence | Data Science
التخصص
علوم الكمبيوتر وتكنولوجيا المعلومات
نوع التعليم
داخل الحرم الجامعي
توقيت
لغة الدورة
إنجليزي
عن البرنامج

نظرة عامة على البرنامج


Doctor of Philosophy in Data Science (By Research)

Programme Overview

The Doctor of Philosophy in Data Science gives broad exposure to key concepts and tools from Data analytics, AI, Machine Learning, and more knowledge and abilities to conduct data science-related research and discovery. The objective of this program is to discover information and facilitate innovation from complicated data and to discover in-depth knowledge of data-driven science about research and scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured. The program aims to produce data research professionals who are passionate about drawing meaningful insights from data using data science approach.


Duration

  • Full Time: 3-5 Years
  • Part Time: 4-8 Years

Intakes

  • Ongoing

Brochure

  • Download

Programme Structure

The Doctor of Philosophy in Data Science is fully research-based, which means there are no traditional coursework or lecture modules like in taught programs. Instead, the structure involves stages of supervised research, progress evaluation, and thesis submission:


Programme Components

  1. Research Proposal Development
    • Students begin by preparing and defending a detailed research proposal.
  2. Supervised Research Work
    • Independent research is conducted under the guidance of academic supervisors.
  3. Progress Reports
    • Students submit and present progress updates periodically (usually every 6 months).
  4. Publications
    • Students are encouraged to publish in indexed journals or present at conferences.
  5. Thesis Preparation
    • Compilation of original research work into a doctoral thesis.
  6. Viva Voce (Oral Defense)
    • Final stage where the candidate defends their thesis before an academic panel.

Entry Requirements

Entry Requirements

  • Masters (Level 7 Malaysian Qualifications Framework, MQF) or equivalent AND candidates must have completed at least one of their previous studies (Bachelor/Masters (Level 6 or Level 7 MQF)) in Computing or related to Computing.

Additional Requirements

  • There is no direct entry from Bachelor’s degree level (MQF Level 6) to Doctorate (MQF Level 8) by research. Candidates with a Bachelor’s degree (MQF Level 6) who are registered for a Master’s program (MQF Level 7), may apply to change their study registration to a Doctoral program (MQF Level 8) by research subject to the following conditions:
    • Application for exchange is within one year of registering for the Master’s program (Level 7 MQF) for full-time candidates and two years for part-time candidates;
    • Have demonstrated competence and ability in conducting research at the Doctoral level (Level 8 MQF) through thorough internal evaluation by the HEP; and
    • Approval from the PPT Senate.
  • PPT can accept excellent Bachelor’s graduates (MQF Level 6) in the field of Computer Science or related to Computer Science or related fields for direct admission to Doctoral program (by research) Level 8 MQF with the following conditions:
    • Students obtain a first class Bachelor’s qualification (MQF Level 6) or equivalent; or
    • Obtain a Cumulative Grade Point Average (CGPA) of at least 3.67 or equivalent from an academic program or Technical and Vocational Education and Training (TVET) program; and
    • Thorough internal evaluation by PPT; and
    • Received approval from the PPT senate and was accepted as a candidate for the Doctoral program (Level 8 MQF). Students need to show appropriate progress during the candidature period.

International Student Requirements

  • Have evidence of good oral and written English proficiency. For example scale 6.0 for /international English Language Testing System (IELTS)/equivalent.

Career Opportunities

  • Data Scientist
  • Big Data Analyst
  • Machine Learning Engineer
  • Mining Analyst
  • Data Modeler
  • Data Architect/Engineer
  • Qualitative Analyst

Program Aim

The program Doctor of Philosophy in Data Science will produce professionals who are:


  • Knowledgeable and skillful in the theory and practice of areas of Data Science with the concept of research work.
  • Competent to practice technically and process interpersonal skill to communication making on various situations and responsibilities during their research work.
  • Capable to work ethically and adopt digital and analytical skills to lend support Data Science professional in their specialty.
  • Able to adopt the autonomy and responsibilities with the excellent leadership skills that is useful for industrial needs in the field of Data Science.
  • Efficient to utilize personal skill to undergo entrepreneurial work in Data Science field effectively.

Subject Highlights

Sl.No. MQA Subject Code Subject Name Credits
1. PHDDS 101 Research Methodology NA
2. PHDDS 102 Data Analysis and Thesis Writing NA
3. PHDDS 103 Research Work (Any one of the following specialties) NA
· Data Mining
· Knowledge Management
· Data Analytics
· Business Intelligence
· Artificial Intelligence
· Data Visualization
· Big Data Integration
· Statistics
· Extensive Computations
· Complex Modeling
· Simulation
· Optimization and Visualization

Accreditation

  • The Doctor of Philosophy in Data Science is accredited by MQA and the Ministry of Education, Malaysia. Reference Number: MQA/PA14151.

Tuition Fee and Scholarship

  • For details about the tuition fees, kindly email or or
  • Eligibility for a scholarship, as well as the amount, is subject to Lincoln University management approval.
  • It’s recommended to consult with the marketing office for more detailed information on potential scholarship opportunities. Kindly email or or

Alumni Network

  • As a graduate of the Doctor of Philosophy (PhD) in Data Science program at Lincoln University College, you can access the university’s active alumni network.
  • Alumni engagement is encouraged through platforms such as LinkedIn groups, virtual and in-person reunions, and LUC-hosted events.
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