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  • Further Topics in Health Data Science

    Module code: MD7476 This module will extend your knowledge to more advanced data science topics as well as exposing you to a wider variety of topics.  You will take one mandatory teaching week (Advanced Data Science).

  • Further Topics in Health Data Science

    Module code: MD7476 This module will extend your knowledge to more advanced data science topics as well as exposing you to a wider variety of topics.  You will take one mandatory teaching week (Advanced Data Science).

  • Overview of Data Science Practice

    Module code: MA7441 Data science is the process of extracting reliable insights and conclusions from data.

  • Overview of Data Science Practice

    Module code: MA7441 Data science is the process of extracting reliable insights and conclusions from data.

  • Overview of Data Science Practice

    Module code: MA7441 Data science is the process of extracting reliable insights and conclusions from data.

  • SciArt and Big Data Analysis

    Module code: CO2109 This interdisciplinary module explores the intersection of science, art, and data, equipping you with the necessary skills to analyse, visualise, and communicate complex information creatively.

  • SciArt and Big Data Analysis

    Module code: CO2109 This interdisciplinary module explores the intersection of science, art, and data, equipping you with the necessary skills to analyse, visualise, and communicate complex information creatively.

  • Foundations of Health Data Science

    Module code: MD7475 This module will provide an outline of the workflow of a typical data science project, from the formation of questions to the communication of results.

  • Foundations of Health Data Science

    Module code: MD7475 This module will provide an outline of the workflow of a typical data science project, from the formation of questions to the communication of results.

  • Foundations of Health Data Science

    Module code: MD7475 This module will provide an outline of the workflow of a typical data science project, from the formation of questions to the communication of results.

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