Data Analytics and Applied Machine Learning

Cerrar explora esta secciónHamburguesa explora esta secciónMENU / Your training

Icono formularioWe send you the brochure

The marked fields include an error or haven't been filled correctly.

    WHAT YOU WILL LEARN

    COURSE CONTENT

    Data analytics evolution

    Automatic Learning

    Classification and Regression

    Over adaptation and VAlidation

    Model Evaluation

    Models: Linear/ Linear regression, KNN, Bayes, Trees, Ensembles, Neuronal Network

    Grouping

    Hierarchical grouping and K- means

    Decision of the grouping number

    Association number

    Evaluation of the association norms

    Apriori and its extensions

    null

    STRUCTURE OF THE COURSE

    YOUR COURSE PLAN

    The course is structured as follows: 

    INTRODUCTION: participants personal work to get initiated into the topic of the course.

    COURSE MODULES: in order to work on the content, the course is divided in three sections. Each section combines one live video conference class with other activities to be done before and/or after the video conference. Therefore, each section is organized as follows:

    • 1h30’ live video conference 
    • 30 minutes of personal work to do activities prior to / after the live session

    CLOSING SESSION: 1 hour video conference session to sum up the program, solve those questions arisen during the course and provide general feedback about the requested activities.

    Course calendar

    HOW YOU WILL LEARN

    METHODOLOGY

    The methodology of this course, as al Deusto Summer School courses, will be based on the University of Deusto Learning Model, adapted to distance learning. This model enables the autonomous learning of the students and encourages the development of knowledge, skills, attitudes, capacities and values.

    More information

    01

    LEARNING METHODS COMBINED

    Combination of live video conference classes with online learning through resources and activities on the university's learning platform.

    02

    DIVERSE RESOURCES

    Use of learning materials in different formats for the presentation of theoretical content.

    03

    ACTIVITIES BEYOND THEORY

    Carrying out different learning activities to verify the acquisition of both theoretical and practical knowledge and the acquisition of skills.

    04

    STUDENTS FOLLOW-UP

    Monitoring of and supervision of the work of the students.

    LECTURER

    null

    LECTURER

    Enrique Onieva holds a PhD in Computer Science (University of Granada, 2011). He joined Deusto Institute of Technology (DeustoTech) in 2013, where he has conducted diverse research in the application of soft computing techniques to the field of intelligent transportation systems. He is also professor at the University of Deusto.

    SEE PROFILE

    CERTIFICATE OF PARTICIPATION

    Upon completion of this course participants will obtain a certificate of participation in this course. 

    CONTACT US

    Deusto_Estudiantes

    CONTACT US

    DEUSTO SUMMER SCHOOL

    Web

    deusto.es/summerschool


    Address

    Ada. Universidades, 24. 48007, Bilbao


    Contact

    summerschool@deusto.es

    Data Analytics and Applied Machine Learning

    Related programmes