The course contains the description of the best practices of AI & ML integration in up-to-date fuel and energy sectors. The major part of the course is industry-oriented practical training, which provides necessary knowledge and skills in the sphere of data analysis and machine learning to manage real story problems of the industry.

The main goal of the course is to provide a comprehensive understanding of the theory and practice of intelligent systems and the application of machine learning methods in the sphere of power industry (in Smart Energy Systems).

Within the framework of the discipline students will carry out their own theoretical and experimental research in the field of artificial intelligence, machine learning, design of Smart Energy Systems and master the skills of data representation, processing and analysis.

The target audience of the course covers bachelor and master students, pursuing the degree in Computer Science, Power Engineering and Electronics.

Project goals:

• Acquiring of new knowledge, practical experience along with mastering the forefront technologies in power industry and mathematics and software engineering;
• Establishing business contacts between the students and industrial partners - leading energy and fuel companies of Russia;
• Getting experience in multi-project work disciplinary;
• Dealing with real-story challenges, that high-technological energy and fuel companies are currently facing;
• Publishing the project results in peer-reviewed scientific transactions.

Prerequisites:

Bachelor or Master Degree in the field of Computer Science, Power Engineering or Electronics, CV, PC.

At the End of the Internship:

• Certificate from UrFU;
• Unique experience of international cooperation;
• The most outstanding participants will publish the project results in peer-reviewed scientific journals with the leading university professors;
• Letter of recommendation from the Industrial partner.