Data analytics is one of the most in-demand skills in today’s workplace, spanning every sector from finance and healthcare to technology and public service. This course provides a practical, introductory grounding in how to responsibly manipulate, analyse, and communicate the findings of data analysis.
Learning Outcomes:
- Define key data science concepts and describe basic data variable types, structures, and categories.
- Import, clean, organise, and aggregate data using SQL, R, Python, and Excel.
- Describe and differentiate between types of data analysis, including descriptive, predictive, and prescriptive analysis.
- Apply data aggregation and interpretation metrics, and conduct exploratory data analysis.
- Create and interpret data visualisations, selecting appropriate chart types to represent data accurately.
- Derive meaningful conclusions from data visualisations and communicate findings effectively.
- Apply responsible analytics practices, including data privacy laws, handling of PII, and identifying types of bias.
