Data mining course with Orange

This course in data mining with Orange provides a complete introduction to this open source data analysis tool. From its definition to its advantages and functionalities, you will learn to load, prept, explore, model and display data efficiently. Through workflows and customizable widgets, you will acquire the ability to handle and analyze complex data sets, identify patterns and structures, and perform predictive modeling. In addition, Orange Data Mining apart from being accessible to everyone due to its Open Source nature, also stands out for its ease of use and its robust set of functionalities. In addition, you will have a teaching team specialized in the field.

- Understand what Orange Data Mining is and its advantages. - Dominate data load and preprocessing in Orange. - Use visual programming to analyze data effectively. - Explore and visualize data to identify patterns and trends. - Apply predictive modeling techniques in Orange. - Build efficient data workflows. - Customize widgets and channels to obtain specific results.

The main professional outputs of this course in data mining with Orange will allow you to opt for roles in data analysis, data science, data engineering and consulting in companies from various sectors, including technology, finance, health and marketing. They can also find opportunities in academic institutions and research centers.

When completing this course in data mining with Orange you can apply data mining techniques using Orange Data Mining in a variety of contexts. You can load, prepock, explore and visualize data efficiently, as well as build and evaluate predictive models. This training will equip you with practical skills to address data analysis problems in your professional career or personal projects.

This course in data mining with Orange is designed for students, professionals and database enthusiasts, artificial intelligence and business analytics that wish to acquire skills in the use of Orange Data Mining. Previous knowledge in data mining is not required, but it is useful to have a basic understanding of statistics and programming.

This training is not included in the scope of official regulated training (Infant Education, Primary Education, Secondary Education, Official Professional Training FP, Baccalaureate, University Degree, Official University Master and PhD). It is therefore a complementary and/or specialization training, aimed at acquiring certain skills, skills or aptitudes of a professional nature, being able to be barely as merit in workbags and/or opposition competitions, always within the complementary training section and/or continuous training being always essential to review the specific requirements of the public labor stock of the public labor stock market.