Postgraduate Certificate in Data Science (Online)
Live Webinar – 12 December 2023, 4pm (NZST)
A Bachelor of Science with a major in Computer Science or Statistics from this University or an equivalent qualification with a GPA of 4.0 or higher in 75 points above Stage II
Next Start Dates
- 26 February 2024 (applications close 12 February 2024)
The PGCertDataSci aims to meet the growing global demand for data scientists by offering you a part-time but intensive data science qualification on your previous undergraduate qualification in either Statistics or Computer Science. This postgraduate certificate also provides you with an alternative pathway into the Master of Data Science.
The Postgraduate Certificate in Data Science is a 60-point programme consisting of two 30-points courses. Each course runs over a 12-week Semester, enabling you to complete this programme one course at a time in as little as two semesters.
To complete this programme, all students must take DATASCI 709 Data Management, and either STATS 709 Predictive Modelling or COMPSCI 717 Fundamentals of Algorithmics. If you have a previous qualification in Computer Science you will take STATS 709, and if you have a previous qualification in Statistics, you will take COMPSCI 717.
|DATASCI 709||Data Management||Data management is the practice of collecting, preparing, organising, storing, and processing data so it can be analysed for business decisions. The course will use R and SQL to illustrate the process of data management. This will include principles and best practice in data wrangling, visualisation, modelling, querying, and updating.||
|STATS 709||Predictive Modelling||Predictive modelling forecasts likely future outcomes based on historical and current data. Following an advanced introduction to statistics and data analysis, the course will discuss concepts for modern predictive modelling and machine learning.||
|COMPSCI 717||Fundamentals of Algorithmics||Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: 15 points from COMPSCI 120 or equivalent and 15 points from COMPSCI 130 or equivalent.||
As a graduate of the PGCertDataSci, you will be able to:
- apply principles and best practice from data governance, management, predictive modelling, machine learning, and statistical analysis to relevant domains
- explore data structures to design efficient solutions to computational problems in data science
- critically analyse data and data models for their appropriateness and limitations to forecast future outcomes
- take into account ethical considerations and evaluate the impact of their findings on culture, economy, environment, and society
*Our programme Advisors will provide all official programme information, including regulations about entry, enrolment, course fees, examinations and requirements for degrees, diplomas and certificates as per the University Calendar. Please note that the programme fees are indicative and estimates only. Fees are set in advance of each calendar year and will be updated on this website. Fees are inclusive of 15% GST, but do not include the Student Services Fee course books, travel and health insurance, or living costs. Fees will be confirmed upon completion of enrolment into courses.
Postgraduate Certificate in Data Science – Enquire Now
* indicates a required field
In a previous blog post, we outlined why a sufficient knowledge of construction-specific contract law is essential to being a successful project manager and/or industry professional. The University of Auckland Engineering School in partnership with...
Contracts are the foundation of any engineering project: outlining the rights, obligations, and responsibilities of all parties involved. Well-structured and well-understood contracts provide clarity, ensure accountability, and minimise the potential for lengthy and costly disputes.
Starting a new project? Agile, waterfall, and Kanban are three popular project management methodologies used in organizations. Each has its own strengths and weaknesses, and their suitability for cross-functional projects may vary.