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Doctor of Philosophy in Data Science

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Lincoln University College

Doctor of Philosophy in Data Science

university icon
Lincoln University College

Doctor of Philosophy in Data Science

Qualification
Doctoral Degree (PhD)
Duration
3 years
Intake
AugAug
English Requirement
IELTS 6.0
Offer Letter
Free
Class Type
Physical
Course Fee for International Students
First year from MYR 16,500 excludes 6% SST & other fees
Estimated total tuition from ~MYR 49,500 3 years programme
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The Doctor of Philosophy (Ph.D.) in Data Science degree at Lincoln University College Malaysia teaches advanced research methods and applications. Graduates perform unique research in fields such as machine learning, data mining, and big data analytics, helping to enhance knowledge in data science and its applications across sectors. This program prepares graduates for leadership positions in academia, research institutions, or the private sector, where they can drive innovation and make major contributions to addressing difficult data-driven issues.

Career Opportunities:

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

Program Aim:

  • Knowledgeable and skilled in the theory and practice of Data Science, including the notion of research work.
  • Competent in using technical and interpersonal skills to communicating in a variety of contexts and responsibilities while doing research.
  • Capable of working ethically and applying digital and analytical skills to assist Data Science professionals in their field.
  • Capable of accepting autonomy and responsibility while demonstrating strong leadership abilities, which are valuable for industrial demands in the field of data science.
  • Efficient in using personal skills to effectively pursue entrepreneurial activity in the field of data science.

Suggested topics to look into:

  • Creating innovative data analysis methodologies.
  • Investigate machine learning algorithms for predictive modeling.
  • Investigate large data management and processing.
  • Examining data ethics and privacy issues.
  • Investigating the uses of data science across diverse businesses.
  • Investigating optimization techniques for large-scale data sets.
  • Investigating artificial intelligence methods for data analysis.
  • Creating novel data visualization approaches.
  • Investigating multidisciplinary cooperation for data science research.
  • Investigating the effects of new technology on data science approaches.
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