Data Analytics without Programming

 Studierende / Forschende / Lehrende

 Online theory and in-person practical work

 Kurs auf Englisch, Unterstützung auf Englisch und Französisch

 FS 2022

 Keine technischen Kenntnisse vorausgesetzt

Society is undergoing a relentless digital transformation and most aspects of daily life are now quantified. The availability of such huge quantities of data makes its analysis all the more important in all domains. However, many do not have the necessary skills to write code for manipulating data and even less to make use of advanced techniques such as machine learning.  For this reason, our course aims at teaching how to prepare and analyze data in general and via machine learning techniques without coding.

  • Ziel

    The goal of this course is to be able to analyze data in a descriptive way or with machine learning algorithms without the need to learn to program.

  • Inhalte und Themen

    In particular, the students will:

    • Learn what data analytics and big data are, and why they are important;
    • Learn to perform descriptive analytics and to plot data appropriately with a brief introduction to Tableau;
    • Learn what machine learning (ML) is and its impact on data analytics;
    • Learn how to use RapidMiner Studio to perform data analysis with machine learning without coding.
  • Form, Datum und Ort

    The course is organised as follows:

    • theoretical part online (with videos and tutorials),
    • practical work face-to-face.

    Face-to-face Sessions:

    • Tuesday 3:15 - 5:00 PM, PER 17-room 001
    • First session: 29.03.2022
    • For more details you can view the TimeTable
  • Voraussetzungen

    No particular computer skills are required.

  • Validierung

    The acquisition of ECTS credits is possible and optional by passing an exam at the end of the course. The format of the exam will be specified at the beginning of the course.

  • Verantwortliche

    Eliane Maalouf

    Maurizio Caon

Anmeldung  

Anmeldungen ab dem 5. September möglich.

Kontakt

Eliane Maalouf

eliane.maalouf@hefr.ch

Maurizio Caon

maurizio.caon@hefr.ch

In Zusammenarbeit mit