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Government, private enterprise and science have always been data-driven, what is changing dramatically is the sheer amount of data now generated. Data Science, sometimes also referred to as Big Data, is a rapidly evolving field which studies how to organize, analyse and communicate relevant data through appropriate data visualisations as well as written and oral communications. While data science鈥檚 technical foundations arise from Mathematics, Statistics and Computer Science, the area is fundamentally both multi and interdisciplinary. It is most often performed in collaborations across disciplines to bring together the necessary skills and relevant application knowledge. Those with a technical background related to data science need an understanding of the data relevant to the particular problem application area. Those with expertise in the application area must acquire the relevant technical knowledge in order to effectively and accurately make use of data science tools and methodologies.

This course covers foundational data science concepts, tools, methodologies and visualisation. Students will learn how to extract knowledge from data through hands-on experience with common data science programming tools and methodologies. They will create data visualisations to conduct exploratory and confirmatory data analysis. And will gain an appreciation of the breadth of data science applications and their potential value across disciplines.

On successful completion of this course students will be able to:

1. Differentiate between data science algorithms and interpret their appropriate application across disciplines.
2. Apply data visualisations and written communication, tailored to specific discipline audiences, to report a data science project鈥檚 central problem, data analysis, reasoning and conclusions.
3. Identify and apply the appropriate technical processes and problem-solving skills for the successful completion of a data science project.
4. Plan and execute a data science project.