Master of Applied Computing (MAC)

First Intake: August 2020
Intakes: January, March, August

The Master of Applied Computing (MAC) programme by Taylor’s University in partnership CASUGOL is committed to educating the next generation of world-class innovators. In a bid to sustain a culture of empowerment and innovation, it is the program’s mission to develop critical human capital for the knowledge economy as well as forge broader Taylor’s University academic-industry partnerships.

Students of Master of Applied Computing (MAC) will have the opportunity attend an industry-bridging programme on Artificial Intelligence (AI) / Machine Learning or Data Science supported by CASUGOL.

Through the extensive practical / hands-on sessions led by industry experts from CASUGOL, students can acquire knowledge, and technical know-how based on the latest market trend, and industry best practices.

Upon completion and fulfilling all requirements, students will receive an International Certificate of Competency and be recognized as either an Advanced Data Science Professional (ADSP) or Certified Machine Learning Expert (CMLE) depending on the student’s area of specialisation.

This initiative is in line with the academic partnership between Taylor’s University and CASUGOL to provide Researchers, Academicians, Educators, and Students with the opportunity to receive industry-related education, and get certified in the areas of digital transformation and emerging technologies e.g. Artificial Intelligence (AI), Machine Learning, Data Analytics, and Data Science etc…


Master of Applied Computing Students will:

  • Master the knowledge of the most up-to-date technologies
  • Use a wide array of technical skills to develop software applications that demand performance, reliability, and safety standards.
  • Engage in primary and secondary research.
  • Develop critical reasoning and technical writing skills.
  • Develop professional presentation skills.
  • Receive focused attention from faculty advisors.
  • Practice hands-on exposure to a variety of computer systems, tools and techniques.
  • Receive excellent preparation for seeking careers in software-related computing fields.

Specialisation
Artificial IntelligenceData Science
  • Advanced skills and techniques in artificial intelligence.
  • Research opportunities to solve meaningful industrial problems with artificial intelligence techniques.
  • Advanced research opportunities in artificial intelligence in preparation for doctoral studies.
  • Knowledge and applied skills in data science, big data analytics and business intelligence.
  • Overall understanding of the impact of data science upon modern processes and business.
  • Exposure towards data science tools and techniques, as well as methods of data collection and utilisation, to turn data into useful information via various processes.

  • Unique Selling Point

    • One-year programme
    • Specially design for industrial professionals – Hands-on; Applied; Modular
    • Capstone projects & assignments are mostly industry-based with both industry-academia supervisors. Active involvement of industry in the programme
    • Modules will be taught by academia and industry experts
    • Professional Certification in Data Science and Artificial Intelligence
    • Work with Center for Data Science and Analytics (C4DSA) to earn AI/ DS certificates for wide range of tools (e.g. Hadoop, Spark, Flume, Pig, Hive, etc.). These skills are of high demand in industry
    • Opportunity for non-ICT graduate to move into AI & Data Science
    • Suitable for working adults – take one module at a time during weekends
    • Facilities:Taylor’s Center for Data Science & Analytics – collaboration with C4DSA to provide certification and Hands-on experience in HPC and Big Data Software

    Who Should Join This Programme

    • Undergraduate students
    • Industry professionals – Corporate clients and working adults
    • Non-IT Graduates (Bridging module offered)
    • Micro-credentials and Micro-masters

    Future Career
    Artificial Intelligence SpecialisationData Science Specialisation
    • AI Researcher
    • Intelligence Specialist
    • Consultant
    • AI Data Analyst
    • Machine Learning Programmer
    • Machine Learning Engineer
    • Robotics R&D Engineer
    • Machine Vision Engineer
    • Artificial Intelligence Analyst
    • Deep Learning Scientist
  • Data Engineers
  • Data Analyst
  • Business Analyst
  • Data Scientist
  • Chief Technology Officer (CTO)
  • Data Analytics Manager
  • Business Analyst Manager
  • Data Innovation Manager
  • Machine Learning Scientist
  • Business Process Engineer
  • Data Wrangler / Munger / Miner
  • Business Intelligence Manager
  • Analytics & Reporting Manager
  • Decision Analytics Manager

  • Entry Requirement

    • Bachelor’s degree with CGPA above 2.75; OR
    • Bachelor’s degree with CGPA between 2.75 and 2.50 with 2 years working experience and an interview; OR
    • All Bachelor’s degree with CGPA less than 2.5 and minimum 5 years working experience
    *Accreditation of Prior Experiential Learning (APEL) in accordance to Malaysian Qualification Agency requirement and 2 years managerial/ supervisory experience; OR

    Other academic qualification that are equivalent to the above and recognized by the Malaysian Qualification Agency (MQA) and the Malaysian Ministry of Education.

    For international students: IELTS 6.0 (May join IEN preparatory course and achieve the IELTS score).

    NOTE:
    The following criteria shall apply for working adults applying for Accreditation of Prior Experiential Learning (APEL):
    a) All applicants are subjected to appropriate APEL assessments conducted by the Malaysian Qualifications Agency (MQA)
    b) The APEL provision is only to be applied to Malaysian nationalities

    *Terms and Conditions Apply.
    *All information is subject to change. The above entry requirements serve as a guideline. Readers are responsible to verify the information by contacting the university’s Admissions Department.