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MSc Energy Systems and Data Analytics (ESDA)

  • DeadlineStudy Details:

    MSc 1 year full-time, 2 years part-time, 5 years flexible

Course Description

Energy Systems and Data Analytics MSc provides an academically leading and industrially relevant study of energy systems through the lens of data analytics. Advanced analytics, fuelled by big data and massive computational power, has the potential to transform how energy systems are designed, operated and maintained. You will gain the skills and knowledge to unlock the transformative potential of big energy data and understand how it can reshape the energy sector.

Energy Systems and Data Analytics MSc is the first programme in the UK to combine the study of energy systems with data science. As a student studying this MSc you will gain a broad understanding of energy systems as a whole, covering supply and demand, the interconnectedness and dependencies between different sectors and a multi-vector multi-sector approach to analysis. You will learn about the theory and practice of data analysis, how to write code to manipulate and clean data, to extract insights, and to train models to make predictions from that data. You will gain a theoretical understanding of machine learning and statistical methods such as supervised and unsupervised learning, deep learning methods, and artificial intelligence. This will encompass the strengths and weaknesses of various approaches and the situations in which they are best suited. You will also learn how to deploy these methods and you will gain practical experience of the challenges of working with different data sets relating to energy throughout the programme and modules.

Energy systems are strongly influenced by spatial and geographic features and the course features a dedicated spatial data analysis module to train you in some of the unique aspects of doing data analysis on data with a spatial component.

Entry Requirements

A minimum of an upper second-class Bachelor’s degree or an overseas qualification of an equivalent standard.

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Fees

For fees and funding options, please visit website to find out more.

Programme Funding

UCL offers a range of financial awards aimed at assisting both prospective and current students with their studies.

Student Destinations

Graduates will be ideally placed to gain employment as energy analysts/data scientists in consultancies, utilities, innovative start-ups and government institutions which value expertise in energy systems and have a need for data literate analysts. The ongoing digital transformation of the energy sector means there is a real demand for graduates who can bring the power of machine learning and data science to bear to solve problems in the energy system such as grid resilience, fuel poverty and renewable power forecasting.

You will gain employable skills in data science, machine learning and artificial intelligence as well as expertise in energy systems and energy consumption in the built environment and transport system.

The strong emphasis placed on research and integration of the course with research activities in the department means you will get exposure to state-of-the-art energy research at one of the UK’s leading research centres.

Module Details

Compulsory modules

  • Energy Systems
  • Advanced Machine Learning for Energy Systems
  • Energy Data Analysis
  • Statistics for Energy Analytics
  • Energy Data Analytics in the Built Environment
  • Energy and Transport Analytics
  • Dissertation: Energy Systems and Data Analytics
  • Spatial Analysis of Energy Data

Optional modules

  • UK Energy and Environment Policy and Law
  • Energy, Technology and Innovation
  • Systems Thinking and System Dynamics
  • International Commodity Trade
  • Econometrics of Energy Markets
  • Electricity Market Design for the Energy Transition
  • Applied Bayesian Methods

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