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Competenze & Professionalità

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  1. Insegnamenti

ECO0043 - ANALYTICS AND DATA SCIENCE LAB

insegnamento
Tipo Insegnamento:
Ins. uff. con erogazioni senza cop.
Durata (ore):
30
CFU:
4
SSD:
Indefinito/Interdisciplinare
Sede:
BRESCIA
Url:
Dettaglio Insegnamento:
Analytics and Data Science for Economics and Management/PERCORSO COMUNE Anno: 2
Anno:
2025
Course Catalogue:
https://permalink.unibs.it/suacds/afcc/2025?corso=...
  • Dati Generali
  • Syllabus
  • Corsi

Dati Generali

Periodo di attività

Secondo Quadrimestre (02/03/2026 - 09/06/2026)

Syllabus

Obiettivi Formativi

The educational objectives are consistent with those characterizing the degree program in “Analytics and Data Science for Economics and Management” in which the course is inserted. In particular, the focus in on providing students with the necessary computer and technological knowledge to know, model and manage complex phenomena.
Real case studies and applications are proposed in socioeconomics and management fields.
In the end of the course, students will have gained a range of technical skills and practical knowledge related to data analytics and data science, along with important transferable skills that can be applied to a variety of professional contexts.

In detail, students will gain the following skills:

1) Knowledge and understanding: Students will gain familiarity with tools used in analytics and data science and will be able to explain the importance of using appropriate tools and software to manage, analyze and visualize data effectively.

2) Applying knowledge and understanding: Students will develop practical skills in data analysis, including data preparation, manipulation, cleaning, and visualization.

3) Making judgements: Students will develop critical thinking skills when evaluating data sources, assessing the quality of data, identifying the best analytical tools and and interpreting results.

4) Communication skills: Students will develop communication skills, being able to present complex technical information to both technical and non-technical audiences.

5) Learning skills: Students will develop the ability to work autonomously to obtain knowledge from data analytics and data science practices.

Prerequisiti

Basic knowledge of coding and data analysis

Metodi didattici

Practical lessons in lab and project works

Verifica Apprendimento

Students skills will be assessed in their ability of solving a set of in-class exercises and applications.
Subject to availability, collaborations with external partners (e.g., for the provision of certifications related to tools and technologies for analytics and data science) may be activated during the academic year. In such cases, the external certification may be adopted as the final assessment component.

A pass grade will be awarded to students who meet the following requirements:

a) have provided documented evidence of completion of all required learning activities;

b) have attempted the external certification exam (if applicable) and either:
– successfully passed the exam, or
– achieved a score of at least 60% of the total;

Students who do not reach the 60% threshold or have not attempted the external certification exam may still be awarded a pass upon submission of an individual project on topics relevant to the course syllabus, subject to prior approval by the teacher and agreed upon sufficiently in advance.

Testi

Course materials provided by the teacher.

Contenuti

This course provides, by means of practical applications, an introduction to various tools and technologies used in analytics and data science.

Lingua Insegnamento

English

Altre informazioni

If the computer lab cannot be used, students are required to bring their own laptops

Corsi

Corsi

Analytics and Data Science for Economics and Management 
Laurea Magistrale
Corso ad esaurimento
2 anni
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