Master of Science (Data Science & Analytics)

Overview

Master of Science (Data Science and Analytics) programme will equip graduates with the core Data Science and Analytics knowledge required to work with large and complex data sets in multidisciplinary fields. The core modules of the programme include Data Mining, Data Analytical Programming, Machine Learning for Data Science, Big Data Storage and Management and Data Visualisation and Visual Analytics. Graduates will have strong capabilities to integrate the specialised filed requirements with Data Science and Analytics to improve and transform the Data Science process within an organisation.

For successful completion of Master’s degree each candidate should publish minimum of two research articles in Scopus indexed journals with Lincoln University College affiliation.

Program Aim

The programme Master of Science (Data Science and Analytics) will produce professionals who can be able to:

• Produce knowledgeable and be technically competent in the field of Data Science and Analytics in line with industry requirement locally and globally.
• Perform well as a team player, demonstrate good leadership qualities in an organization, and be effective in communication.
• Solve problems related to the field of IT creatively, innovatively, ethically, using numerical and technical skills, and through sustainable approach to solve Data Science and Analytics related problems.
• Demonstrate entrepreneurship skills and recognize the need of lifelong learning, as well using a broad range of information, media, and technology applications for successful career advancement.

Career Opportunities

The Master of Science (Data Science and Analytics) programme blends scientific knowledge with practical learning to prepare you to further your career in today’s data-driven environment. Their program-acquired abilities will prepare them for graduate-level positions in this industry. The most prominent positions held by someone having this degree are listed in below:

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