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Data science essentials for the energy sector: the case of wind energy
Data science essentials for the energy sector: the case of wind energy
Harness the power of data in the digitalized energy sector
About this course
The green revolution is underway and it is fueled by an increasingly high share of weather dependent renewable energy sources, such as wind and solar photovoltaics. Renewables sources raise a number of challenges, stemming from their variability in time and space, broad spatial distribution, different capacities and the uncertainty in predicting their production. Some of the key challenges are: How should renewables be integrated into the existing power system; How can the renewables remain price competitive with respect to fossil fuels; and how can the efficiency and reliability of renewable power plants be improved across all life cycle stages.
Increasingly, these challenges are being investigated using digitalization, which is fueled by increases in computer connectivity and decreases in the cost of computer storage and processing power. The techniques used for these investigations are emerging from new fields of research, leading to new professions. A pivotal new area is the field of data science.
Data science combines data management tools, which help document, organize, and manage data, with statistical methods that are used to extract information and identify patterns that can be transformed into new insights, products, services, or processes, i.e., into value. To support data science, there is an ongoing effort to digitize infrastructures and assets, which helps to create the raw multi-disciplinary and multi-sectoral data that is needed for data science. Once this data is created, novel algorithms need to be identified to extract the key information from data.
Is this course for you?
This course is designed for future energy domain professionals, who wish understand essential data science tools, allowing you to select the best data science tool for different analyses of multi-disciplinary and multi-dimensional data sets. You will also learn about the data lifecycle, which will enable you to produce and distribute datasets that can be used by others in the industry.
How will the course increase my opportunities?
In this new digitalization era, to be familiar with data stewardship and equipped with data science essentials is an added value as energy domain scientist when applying for a job in both industry and academia.
Data is an asset and skills in data stewardship and knowledge in data science are seen as a key competence to unveil new insights from new information and create competitive advantage. As a domain specialist your expertise is crucial in order to formulate a problem, identify and collect and analyse data, discuss and interpret results to foresee innovation products, services, or business processes.
What will I learn?
The course will provide you with the competences and knowledge necessary to extract important information from energy sector data, and encourage the innovative thinking required to make significant and strategic changes that minimize costs and maximize efficiency, outcomes, and values.
During the course you will be introduced to basic data science skills including Artificial Intelligence with different types of Machine Learning techniques. As a relatively mature technology, wind energy will provide good case studies from different stages of the lifetime cycle of wind energy power plants that will allow you to put your new competences and knowledge to work on real life cases.