Artificial Intelligence and Data Analysis
Introduction
Artificial Intelligence (AI) refers to the process by which computers analyse data, perform actions and learn from experience. The Course “Artificial Intelligence and Data Analysis” covers two distinct parts of the field, with no prior knowledge or experience required:
Data analysis is the process of extracting useful information from large datasets. It includes elements such as formatting, cleaning, analysing and interpreting data. The seminar includes elements of descriptive statistics and data visualisation.
Starting from scratch, with no previous experience in the field required, we will show how to handle a large dataset so that we can then group it (clustering), classify it (classification) and use it to train (training) various machine learning models in order to make predictions (forecasting).
The Course briefly presents the main categories of machine learning (1. Supervised Learning, 2. Unsupervised Learning and 3. Reinforcement Learning) and the most important related methodologies. Emphasis is placed on applying the methodologies in practice using specialised open-source machine learning and data analysis software, on case studies, and on clustering and forecasting in the energy sector. The seminar aims to build core skills among participants and provides the necessary methodological and practical knowledge of artificial intelligence and data analysis. It is clear that, in order to meet these needs, continuous training of the country’s workforce is essential, so that it can acquire new skills adapted to new technologies and to the ever-growing number of data sources in the energy market.
Educational Material