Energy Systems and Data Analytics MSc 12 months Postgraduate Programme By UCL |TopUniversities
Programme Duration

12 monthsProgramme duration

Tuitionfee

39,600 GBPTuition Fee/year

Application Deadline

25 Jun, 2027Application Deadline

Starting Month

SepStarting Month

Programme overview

Main Subject

Built Environment

Degree

MSc

Study Level

Master's

Study Mode

On Campus

Designed in collaboration with industry, the Energy Systems and Data Analytics MSc equips you with the advanced skills needed to support net zero goals, combining technical knowledge of energy systems with expertise in data science, artificial intelligence (AI), advanced machine learning and deep learning. 


 During your degree, you develop the expertise to:  


  • Use data science, machine learning and AI to extract insights from large and diverse datasets, including energy demand, electricity prices, weather and climate data, building energy data and spatial/GIS datasets. 
  • Analyse complex energy systems, including supply, demand, sector interdependencies and infrastructure planning. 
  • Apply modelling tools to support decarbonisation, smart grid optimisation and low-carbon transitions. 
  • Evaluate and deploy methods in supervised and unsupervised learning, advanced machine learning, deep learning and predictive analytics, using tools such as Python and machine learning libraries. 
  • Work with spatial data and spatial analysis methods to understand the geographic and place-based dimensions of energy systems, including applications in electric vehicles, the built environment and low-carbon infrastructure planning. 


This multidisciplinary course responds to the growing need for energy professionals who can turn complex data into insight and action. Throughout the degree, you gain hands-on experience working with sector-relevant datasets, analytical tools and applied case studies in areas such as energy forecasting, smart energy systems, electric vehicles, the built environment, decarbonisation pathways and low-carbon infrastructure planning, preparing you to contribute to innovation in decarbonisation and smart energy systems.

Programme overview

Main Subject

Built Environment

Degree

MSc

Study Level

Master's

Study Mode

On Campus

Designed in collaboration with industry, the Energy Systems and Data Analytics MSc equips you with the advanced skills needed to support net zero goals, combining technical knowledge of energy systems with expertise in data science, artificial intelligence (AI), advanced machine learning and deep learning. 


 During your degree, you develop the expertise to:  


  • Use data science, machine learning and AI to extract insights from large and diverse datasets, including energy demand, electricity prices, weather and climate data, building energy data and spatial/GIS datasets. 
  • Analyse complex energy systems, including supply, demand, sector interdependencies and infrastructure planning. 
  • Apply modelling tools to support decarbonisation, smart grid optimisation and low-carbon transitions. 
  • Evaluate and deploy methods in supervised and unsupervised learning, advanced machine learning, deep learning and predictive analytics, using tools such as Python and machine learning libraries. 
  • Work with spatial data and spatial analysis methods to understand the geographic and place-based dimensions of energy systems, including applications in electric vehicles, the built environment and low-carbon infrastructure planning. 


This multidisciplinary course responds to the growing need for energy professionals who can turn complex data into insight and action. Throughout the degree, you gain hands-on experience working with sector-relevant datasets, analytical tools and applied case studies in areas such as energy forecasting, smart energy systems, electric vehicles, the built environment, decarbonisation pathways and low-carbon infrastructure planning, preparing you to contribute to innovation in decarbonisation and smart energy systems.

Admission Requirements

180+
76+
4.5+
7+
A minimum of an upper second-class Bachelor’s degree or an overseas qualification of an equivalent standard.

25 Jun 2027
1 Year
Sep

Tuition fees

Domestic
21,500 GBP
International
39,600 GBP

Scholarships

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