The course is aimed at economists and statisticians from central banks who are interested in studying advanced topics in seasonal adjustment and in the efficient application of JDemetra+. Prior knowledge and/or experience of time series analysis in general and seasonal adjustment in particular are highly recommended.

The expert panel is aimed at central bankers as well as regulators and supervisors with an interest in helping develop best practices in big data mining and management. Participants will be expected to make an active contribution to the discussions and will be invited to present and discuss current issues in machine learning, artificial intelligence and big data in their own jurisdiction.

The course is aimed at economists and statisticians who are interested in seasonal adjustment and, in particular, in the application of JDemetra+. Prior knowledge and/or experience of time series analysis in general and seasonal adjustment in particular are welcome but are not a prerequisite for participation.

The course is designed for staff working in information technology, statistics or research departments at central banks and regulatory and supervisory authorities with an interest in applying machine learning methods with Python. It is not aimed at those who already have extensive and advanced knowledge of Python.

Indeed, little prior knowledge is expected, and the necessary Python skills are covered at the beginning, making the course suitable for previously inexperienced staff. It may be interesting for those who wish to switch from the programming language R to Python.