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The Chinese University of Hong Kong
This course presents an introductory roadmap into the newly emerged and rapidly evolving field of data science, with the objective of introducing the problem-solving mindset in a data-intensive context.
The course projects data science as a productive synthesis of its parent disciplines, including mathematics, statistics, computing, data mining, system science and data visualization, etc. Such a productive synthesis is applicable across many fields to bring about scientific discovery through data-intensive, analytical methods. This course aims to help navigate students in taking more advanced courses in its parent disciplines to build up their expertise in data science. We cover topics including:
History and impact of Data Science.
Collecting Data: sources, types and categorization of data.
Visualising Data: summary statistics, data display, data dictionaries, schema and graphical visualization.
Analysing Data: pattern recognition, correlations and relationships, hypotheses testing, statistical significance.
Investigating Data: data mining, machine learning, inference, meta-data, modeling, eliciting meaning and validation.
Applicational contexts: Examples of useful applications from case studies.
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Report, mid term, hw and final.
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