Master of Analytics (Massey University)
Course Information
Description
The Master of Analytics programme will equip candidates with both the technical abilities and competence in devising data-driven solutions. These are the skills needed to transform massive amounts of data into intelligence that is useful for crucial organisation decisions.
The course will cover the fundamental theoretical concepts in analytics as well as the latest and cutting-edge technological applications in the industry such as Python and R programming, together with SQL (Structured Query Language). Candidates will then learn how these tools are applied in the specialisation of their choice.
In the last phase of the programme, candidates will need to complete an applied analytics project, where the knowledge and skills they learnt will be put into practice.
Course Highlights
Complete from 12 Months
With a time investment of 12 months full-time and 24 months part-time, graduate with both a Master of Analytics and SAS industry certification.
Focus Options
Develop analytics finesse across Big Data in Finance and Banking (finance track) or Return on Marketing Investment (marketing track).
Learn Data Analysis Tools And Technologies
Master analytics concepts such as machine learning, data mining, statistics and econometrics, and technologies such as Python, R, SAS and SQL. No prior knowledge required.
Applied Analytics Project
Validate your Master’s journey by through a practicum designed to further enhance your employability.
AACSB-Accredited Business School
Massey University is accredited by the Association to Advance Collegiate Schools of Business (AACSB), awarded to only the top 5% of the world’s business schools.
Entry Requirements
Local Qualifications
- Bachelor’s degree (B+ average)
For more information, https://www.massey.ac.nz/massey/learning/programme-course/programme.cfm?prog_id=93537#.
English Language Requirement
- IELTS 6.5 no less than 6.0
For more information, http://www.massey.ac.nz/massey/international/study‐with‐massey/entry‐requirements/entry‐requirements_home.cfm.
Minimum Age Requirement: 21 years old
International Qualifications:
- See course webpage for more information
Career Opportunities
Information not available
Modules
Part One:
- Introduction to Analytics
- Multivariate Analysis for Big Data
- Practical Data Mining
- Applied Econometric Methods
Part Two (Pick 1):
Finance Track:
- Big Data in Finance and Banking
- Managerial Finance
- Advanced Investment Analysis
Marketing Track:
- Customer Insights
- Return on Marketing Investment
Part Three:
- Applied Analytics Project
The School of Postgraduate Studies may recommend modules for completion within the published duration. The delivery of modules is subject to change and may not follow the sequence as shown above.