Energy Data Analysis (BENV0091)

Key information

Faculty: Faculty of the Built Environment
Teaching department: Bartlett School of Environment, Energy and Resources
Credit value: 15

Restrictions: This module is compulsory and available to MSc Energy Systems and Data Analytics students only.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module focuses on teaching the practical programming skills required for analysis of energy Data sets. You will be taught the fundamental concepts of programming through the leading data science programming language R. You will also be exposed to other languages and software tools such as SQL, Python and Gephi and gain an understanding of when and where each is appropriate, for example using SQL for database access. The main topics covered will be:

路 Fundamental concepts in programming.

路 Working with data, manipulation and cleaning.

路 Strategies for handling missing data.

路 The art of data visualization.

路 Deploying models.

路 Using data creatively to innovate and find new solutions to problems in the energy sector.

Module deliveries for 2024/25 academic year

Intended teaching term: Term 1 听听听 Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study: In person
Methods of assessment: 100% Other form of assessment
Mark scheme: Numeric Marks

Other information

Number of students on module in previous year: 55
Module leader: Dr Amir Gharavi
Who to contact for more information: bseer-studentqueries@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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Useful links

Sustainability

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Important information

The catalogue has been updated with key information about the modules that will run during the 2024/25 academic session. Current and prospective students can browse through the catalogue to consider possible module choices for the coming year.

Please note,听information in the catalogue is听subject to change as teaching and assessment arrangements for 2024/25 may need to be adjusted in line with the University's Feedback and Assessment principles and operating model.

Centrally managed exam durations will be provided on students' individual exam timetables. Arrangements for locally managed exams and in-class activity will be confirmed by the teaching department for the module.

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