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Skills for data scientists - CHE00048M

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  • Department: Chemistry
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2023-24
    • See module specification for other years: 2024-25

Module summary

This module will provide some basic statistical concepts to underpin the applied skills of the other modules. You will also learn how to communicate with technical and non-technical audiences, to interpret the scientific literature of a new field, to work as a consultant for specialists, and to explain the skills that you can offer to potential employers.

Module will run

Occurrence Teaching period
A Semester 1 2023-24

Module aims

Data scientists, whether they work in a single field or across multiple fields, need a range of skills. Data scientists will usually work with specialists in a particular problem, and will need to be able to communicate with those specialists and translate their needs into data science terms. Other skills are also necessary: While not every data scientist needs to be a statistician, some basic statistical knowledge is required in order to interpret results and their associated uncertainties. This module will provide some basic statistical concepts to underpin the applied skills of the other modules. You will also learn how to communicate with technical and non-technical audiences, to interpret the scientific literature of a new field, to work as a consultant for specialists, and to explain the skills that you can offer to potential employers. The module will also cover some basic equality and diversity issues, and how they particularly impact people working in computational sciences. You will also be given a brief overview of how data science is applied in each of the contributing departments.

Module learning outcomes

Students will be able to:

  • Apply the basics of statistical uncertainty and the most common error distribution.

  • Analyse uncertainty in datasets when multiple quantities are involved.

  • Explain how science is practised and communicated.

  • Critique a report from an unfamiliar field and evaluate it against the scientific literature of that field.

  • Author scientific reports for both technical and non-technical audiences.

  • Explain their skills to potential employers, relate them to job specifications, and write a cover letter.

  • Create and evaluate data collection strategies.

  • Evaluate structural biases which may impact both our own judgement and the outputs of methods that we implement.

Module content

  • The normal error distribution

  • Multivariate distributions

  • Understanding least squares

  • Communication to different audiences

  • Visualising data for science communication

  • How science works

  • Equality and diversity issues for data scientists

  • Data collection

  • Ethics and data security

  • Selling your skills

  • Data science for different subject areas

  • Graduate careers events will be included in the program

Indicative assessment

Task % of module mark
Essay/coursework 60
Groupwork 40

Special assessment rules

None

Additional assessment information

Group exercise: Being a consulting data scientist

Oral presentations 5 mins/person + 500 word written reflection

40%

Essay: Evaluating a scientific controversy

2500 word written report

60%

Indicative reassessment

Task % of module mark
Essay/coursework 60
Essay/coursework 40

Module feedback

Feedback will be provided through workshops, online exercises and a formative assessment. Feedback on summative work will be provided within 25 working days of the assessment.

Indicative reading


The information on this page is indicative of the module that is currently on offer. The University constantly explores ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary. In some instances it may be appropriate for the University to notify and consult with affected students about module changes in accordance with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.