Master of Applied Data Science
Computer Science
A course by
UC Online
Advance your expertise with the Master of Applied Data Science from UC Online. This master's degree equips you with advanced technical, analytical, and practical data science skills, including applied research experience, preparing you for a range of careers in the data-driven world.
NZ$62,100
inc GST
Enquire about international pricing
This course starts anytime
NZQA Level 9 Certification (180 Credits)
Post Grad
1
2
3
4
5
6
7
8
9
10
NZ$62,100
inc GST
Enquire about international pricing
This course starts anytime
NZQA Level 9 Certification (180 Credits)
Post Grad
1
2
3
4
5
6
7
8
9
10
Core skills this course teaches
Master advanced data analysis techniques
Apply advanced statistical, computational, and analytical methods to interpret complex datasets.
Develop applied programming skills
Design and implement practical software solutions for data management and analysis, using languages and tools such as Python.
What You're Signing Up For
The Master of Applied Data Science is designed for graduates from diverse backgrounds seeking advanced knowledge in data science. The programme covers data analytics, statistics, computer programming, database management, scalable data science, digital humanities, ethics, and project management. Students develop applied expertise through coursework and a substantial research project and benefit from an online, flexible learning model. Graduates are equipped for high-demand data science roles across industries including government, IT, finance, and research.
Course Content
- Introduction to Data Science: Statistical concepts and application to complex systems.
- Computer Programming: Programming in Python, structured data, functional decomposition, file processing, object-oriented programming.
- Data Management: Database systems, data management in organizations, practical database issues.
- Scalable Data Science: Computational methods for big data and distributed computing.
- Big Data: Techniques for exploring and investigating large datasets.
- Texts, Discourses and Data: Natural language analysis, digital humanities, discourse analysis, topic modeling.
- Data Mining: Classification, regression, clustering, and association using statistical learning and data mining methods.
- Data Ethics: Data ethics, data sovereignty, Te Tiriti o Waitangi, frameworks for ethical practice.
- Project Management Fundamentals: Project delivery skills, stakeholder engagement.
- Computational Social Choice (elective): Voting theory, preference aggregation, judgment aggregation, fair division in data science.
- Elective course option: Another relevant 15-point online course.
- Applied Research Project: Team-based project solving real-world data science problems.
What you need to know first
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Data ScientistBusiness AnalystMachine Learning EngineerMarket Research AnalystFinance Data AnalystGovernment Data SpecialistProject Manager (Data Science)
