Insights from dataLaajuus (4 cr)

Objective

The student will, for example, • identify existing openly accessible data sources (including interfaces) and tools to develop data skills • explain what insights can be obtained from different data • utilize different visuals for different uses such as control charts for identifying exceptions, line charts for predictions and AI visuals (i.e., artificial intelligence visuals) for identifying influencers • create data models and, if necessary, combine different data sets / tables (or queries) to utilize the views produced by the algorithms and create dashboards that utilize the data in different data sets • utilize various executable documents (such as Google Colab) and scripts encoded in the Python programming language when processing data • utilize automated machine learning tools (such as PyCaret) to create models (such as classifiers) and take advantage of the predictions provided by the models

Content

Insights (i.e., meaningful information) are generated from the data by utilizing libraries of programming languages or by using various ready-made software - learn how to automatically produce prediction models and quick insights from data, for example, to help draw attention to deviations and trends. On the basis of various automatically generated models and quick insights, it is possible to form questions and identify variables in the data that should be taken into account, for example, in feature engineering - learn to describe data variables and evaluate the usability of data. In addition, learn how to transform data and combine different data sets to make intentional analyzes and dashboards.

Qualifications

Preferably the following courses of computer science: Introduction to Computing and Programming I - Elementary Programming.