Laboratory "retrieving skills for stem job description and matching with cvs"
A.A. 2023/2024
Learning objectives
Partner: Open Search Group
This Lab is provided within the Data Science for Economics (DSE) degree program.
A small number of students can be admitted due to logistics constraints.
The students (either DSE or non-DSE) must apply for admission. Candidates will be selected by the involved institutions/companies according to CV and motivations.
For application, students must respond to a call that is posted on this website: https://dse.cdl.unimi.it/en/courses/laboratories
The call is typically published a few weeks before the Lab starts.
● Develop text analysis skills for the extraction of skills from job descriptions and CVs
● Develop matching skills between job description and CV skills
● Develop skills in analysing the profiles inserted in the company to determine the winning characteristics of a STEM profile for the Italian market
● Become familiar with the extraction and analysis of data from a structured corporate CRM
● Become familiar with data cleansing
● Explore alternative approaches and being able to use of external data through the integration of public databases
● Become competent in analysing and extracting data using python and use data visualisation tools (QLIK)
This Lab is provided within the Data Science for Economics (DSE) degree program.
A small number of students can be admitted due to logistics constraints.
The students (either DSE or non-DSE) must apply for admission. Candidates will be selected by the involved institutions/companies according to CV and motivations.
For application, students must respond to a call that is posted on this website: https://dse.cdl.unimi.it/en/courses/laboratories
The call is typically published a few weeks before the Lab starts.
● Develop text analysis skills for the extraction of skills from job descriptions and CVs
● Develop matching skills between job description and CV skills
● Develop skills in analysing the profiles inserted in the company to determine the winning characteristics of a STEM profile for the Italian market
● Become familiar with the extraction and analysis of data from a structured corporate CRM
● Become familiar with data cleansing
● Explore alternative approaches and being able to use of external data through the integration of public databases
● Become competent in analysing and extracting data using python and use data visualisation tools (QLIK)
Expected learning outcomes
● NLP skills, in particular skills extraction from Job Ads and CVs
● Creation of an analysis and matching model through the analysis of the database of candidates inserted in the company
● Data Cleaning
● Data Exploration: use and integration of external databases
● Creation of an analysis and matching model through the analysis of the database of candidates inserted in the company
● Data Cleaning
● Data Exploration: use and integration of external databases
Periodo: Secondo trimestre
Modalità di valutazione: Giudizio di approvazione
Giudizio di valutazione: superato/non superato
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Course syllabus and organization
Edizione unica
Periodo
Secondo trimestre
INF/01 - INFORMATICA
SECS-S/01 - STATISTICA
SECS-S/01 - STATISTICA
Attivita' di laboratorio: 20 ore