Master of Data Science

Program Overview

Offered in two formats, the program combines computer science and statistics, allowing students to tailor their learning to their interests. Graduates are highly sought-after in various industries, including technology, finance, and healthcare, and are well-prepared for further postgraduate study.

Program Outline

Master of Data Science (MDataSci) - The University of Auckland

Degree Overview:

The Master of Data Science (MDataSci) equips graduates with the skills and knowledge to transform data into actionable insights driving innovation. This program merges a robust foundation in computer science and statistics, enabling graduates to comprehend, process, and extract value from data effectively. The program fosters critical thinking and reflection, preparing graduates for professional success and further postgraduate study. The MDataSci is offered in two formats:

• 180-point taught masters: Emphasizes both computer science and statistics, ideal for students with backgrounds in both fields.
• 240-point taught masters: Focuses on either computer science or statistics, suitable for students with a strong background in one of these fields.

Outline:

Both program formats comprise a combination of core courses and electives, allowing students to tailor their learning to specific interests and career aspirations.

180-point taught masters:

• Core Courses (60 points):
• Big Data Management (COMPSCI 752)
• Datamining and Machine Learning (COMPSCI 760)
• Advanced Regression Methodology (STATS 763)
• Advanced Data Science Practice (STATS 769)
• Elective Courses (75 points):
• Students can choose from a wide range of electives in computer science, statistics, and related fields.
• Dissertation (45 points):
• Students conduct independent research and present their findings in a dissertation.

240-point taught masters:

• Core Courses (90 points):
• Fundamentals of Algorithmics (COMPSCI 717)
• Advanced Topics in Database Systems (COMPSCI 751)
• Advanced Machine Learning (COMPSCI 762)
• Computational Introduction to Statistics (STATS 707)
• Regression for Data Science (STATS 762)
• Statistical Learning for Data Science (STATS 765)
• Statistical Computing (STATS 782)
• Elective Courses (45 points):
• Students can choose from a wide range of electives in computer science, statistics, and related fields.
• Dissertation (45 points):
• Students conduct independent research and present their findings in a dissertation.

Assessment:

Assessment methods vary depending on the specific course but typically include a combination of:

• Assignments
• Exams
• Projects
• Presentations
• Participation

Teaching:

The program boasts a team of experienced and passionate faculty members who are experts in their respective fields. Teaching methods include:

• Lectures
• Tutorials
• Workshops
• Guest lectures
• Independent study
The program also utilizes a blended learning approach, incorporating online resources and activities to enhance the learning experience.

Careers:

Graduates of the MDataSci program are highly sought-after in various industries, including:

• Technology
• Finance
• Healthcare
• Government
• Research
Potential career paths include:
• Data scientist
• Data analyst
• Machine learning engineer
• Business intelligence analyst
• Data architect

Other:

• The 240-point taught masters is offered only in the March intake.
• The program is designed to provide students with the skills and knowledge necessary to succeed in the rapidly evolving field of data science.
• Graduates of the program are well-prepared for further postgraduate study in data science or related fields.

Conclusion

The Master of Data Science program at the University of Auckland offers a comprehensive and rigorous education in data science, equipping graduates with the skills and knowledge to thrive in the data-driven world. The program's flexible structure, expert faculty, and industry-relevant curriculum empower students to pursue their career aspirations and make a significant impact in the field of data science.