SCIENCE
Postgraduate Certificate in Data Science (Online)
PGCertDataSci
Entry Requirements
Duration
Next Start Dates
- Semester 1:
3 March (Applications close 17 February)
- Semester 2:
21 July (Applications close 7 July)
Full Programme Fees*
$5,302.20 (estimate)
Postgraduate Certificate in Data Science Programme Overview
Who, What, Why
Professor Sebastian Link is the director of the Postgraduate Certificate in Data Science. He is also a Professor of Computer Science, Associate Dean International for Science and Chief Science Officer for DataViadotto.
Learn more about the programme and why it could be ideal for you.
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.
Course Code |
Course |
Description |
Points |
| 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. | 30
|
| 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. | 30
|
| 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. | 30
|
- Apply principles and best practice from data governance, management, predictive modelling, machine learning, and statistical analysis to relevant domainsĀ
- 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
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