Upper University Course in Data Mining (University degree + 8 ECTS credits)

The increasing amount of data handled by a company due to the rise of new technologies and the use of social networks, have generated the demand for professionals who exploit these data with the aim of helping strategic decision making. Through data mining, the necessary knowledge for decision -making can be generated, allowing to discover hidden patterns and performing predictions on data behavior. With this course in Data Mining you can develop the necessary techniques to apply data mining and obtain the necessary analytical skills to extract and evaluate the data in an effective way. We offer a learning environment where the student is the protagonist, supported by tutors specializing in the sector.

- Learn the MINING Data Models and Techniques Applied in a Big Data environment - Know the main statistical analysis algorithms, used in Big Data environment - Acquire the necessary knowledge for distributed data processing in Hadoop - Apply graph theory to social networks analysis - Manage data tools such as Weka Learn to program Data Mining algorithms in R.

We can understand a large range of possibilities in terms of different sectors. In the information age, understanding it, and obtaining a correct interpretation of it is a clear advantage. This advantage wants to be exploited by any company. That is why, thanks to the course in Data Mining, the type of professional profile is able to fit and take advantage of so many options.

This course in Data Mining prepares you to understand the concepts, techniques and tools used in data mining. You will learn to apply algorithms and data analysis methods to discover patterns, trends and hidden relationships in large volumes of information. Skills such as data preparation and exploration are developed, selection and employment of mining techniques and the interpretation of the results

This course in Data Mining is aimed at people interested in acquiring skills and knowledge in the field of data mining. This includes computer professionals, analysts and data scientists, computer science students and any person interested in understanding how to extract valuable information from large data sets.

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.