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Table of contents

• Data Science (CM3005)
  • Professor(s)
  • Topics covered
  • Assessment
  • Module specification
  • Recognition of Prior Learning
  • Syllabus
  • Resources
    • Notes
    • Reading list

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Data Science (CM3005)

By taking this module, you will gain a data science skillset. With these skills, you will be able to write computer programs that can read, process and analyse textual and numerical data. You will be able to generate plots and interactive visualisations of data. You will understand how to apply statistical methods to the interpretation of results. You will be able to use data analysis in the decision-making process. You will also learn about a range of application domains for data science.

Professor(s)

• Dr. Tony Russel-Rose

Topics covered

• Introduction and development environment
• Working with different types of data
• Correlation and regression
• Distributions and significance
• Processing text data
• Decision making based on data analysis: from correlation to causation
• Introduction to data visualisation
• Time-series data visualisation
• Scientific data visualisation
• Case studies: different contexts for data analysis

Assessment

One two-hour unseen written examination and coursework (Type I)

Module specification

• Module specification

Recognition of Prior Learning

• At the time of this writing, you can apply for automatic RPL for this module if you obtain the IBM Data Science Professional Certificate.

Syllabus

• Syllabus

Primary programming language

Python

Resources

Notes

• Visit this page of world-class/notes.

Reading list

• Reading list