Data science for Finance — alignment of Finance and Accounting for the WEI in Lublin with the socio-economic needs and RSI of the Lubelskie province. (Q92371): Difference between revisions

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(‎Removed claim: summary (P836): The aim of the project “Data science for Finance — adaptation of Finance and Accounting for the WEI in Lublin to the socio-economic needs and RSI of the Lubelskie province” is to adapt to the socio-economic needs of the education programme for Finance and to the accounts of WEI in Lublin and to involve employers in the implementation by 09.2020. the project covers the following:activities involving employers in the preparation and implementati...)
Property / summary
The aim of the project “Data science for Finance — adaptation of Finance and Accounting for the WEI in Lublin to the socio-economic needs and RSI of the Lubelskie province” is to adapt to the socio-economic needs of the education programme for Finance and to the accounts of WEI in Lublin and to involve employers in the implementation by 09.2020. the project covers the following:activities involving employers in the preparation and implementation of the programme in response to socio-economic needs.The project is aimed at 45 (M-17/K-28).Date of science in finance.Project tasks:By a team of teachers and employers to develop for the management of the specialty, teaching and other activities resulting from the involvement of employers in the implementation of the project.Involving employers in the teaching process will make it possible to improve training programmes and make the course more attractive.The training offer will be adapted to the requirements of the labour market.The project is in line with the Regional Innovation Strategy for Lubelskie.A selective development model is based on smart specialisations, which are defined as the development of R & D and innovation activities that strengthen the endogenous development potential of the region.One of them is information technology.This is known as “special support”.The date of science, the date of mining, the big data analysis and the business intelligence is the competences of the computer science sector, in order to obtain the additional practical and practical value in a project faced with the social sciences and financial sector of the undertaking. (English)
 
Property / summary: The aim of the project “Data science for Finance — adaptation of Finance and Accounting for the WEI in Lublin to the socio-economic needs and RSI of the Lubelskie province” is to adapt to the socio-economic needs of the education programme for Finance and to the accounts of WEI in Lublin and to involve employers in the implementation by 09.2020. the project covers the following:activities involving employers in the preparation and implementation of the programme in response to socio-economic needs.The project is aimed at 45 (M-17/K-28).Date of science in finance.Project tasks:By a team of teachers and employers to develop for the management of the specialty, teaching and other activities resulting from the involvement of employers in the implementation of the project.Involving employers in the teaching process will make it possible to improve training programmes and make the course more attractive.The training offer will be adapted to the requirements of the labour market.The project is in line with the Regional Innovation Strategy for Lubelskie.A selective development model is based on smart specialisations, which are defined as the development of R & D and innovation activities that strengthen the endogenous development potential of the region.One of them is information technology.This is known as “special support”.The date of science, the date of mining, the big data analysis and the business intelligence is the competences of the computer science sector, in order to obtain the additional practical and practical value in a project faced with the social sciences and financial sector of the undertaking. (English) / rank
Normal rank
 

Revision as of 17:43, 15 October 2020

Project in Poland financed by DG Regio
Language Label Description Also known as
English
Data science for Finance — alignment of Finance and Accounting for the WEI in Lublin with the socio-economic needs and RSI of the Lubelskie province.
Project in Poland financed by DG Regio

    Statements

    country
    Poland
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    EU contribution
    198,679.57 zloty
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    47,683.10 Euro
    exchange rate to Euro
    0.24 Euro
    point in time
    13 January 2020
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    budget
    235,737.5 zloty
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    56,577.0 Euro
    exchange rate to Euro
    0.24 Euro
    point in time
    13 January 2020
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    co-financing rate
    84.28 percent
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    start time
    1 June 2017
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    end time
    30 September 2020
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    beneficiary name (string)
    WYŻSZA SZKOŁA EKONOMII I INNOWACJI W LUBLINIE
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    fund
    European Social Fund
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    summary
    Celem projektu „Data science w finansach - dostosowanie kierunku Finanse i Rachunkowość WSEI w Lublinie do potrzeb społeczno-gospodarczych i RSI woj. lubelskiego” jest dostosowanie do potrzeb społeczno-gospodarczych programu kształcenia na kierunku Finanse i rachunkowość WSEI w Lublinie oraz włączenie pracodawców w jego realizację do 09.2020 r. Projekt obejmuje swoim zakresem: działania włączające pracodawców w przygotowanie programu i jego realizację w odpowiedzi na potrzeby społeczno-gospodarcze. Projekt jest skierowany do 45 st.(M-17/K-28). z nowego naboru 2017/2018, obejmuje swym działaniem cały cykl kształcenia na studiach I st. kierunku Finanse i rachunkowość st. niestacjonarnych kierunku Finanse i rachunkowość I st. na nowoutworzonej specjalności: Data science w finansach. Zadania realizowane w projekcie: Opracowanie przez zespół dydaktyków i pracodawców nowoutworzonej na potrzeby gospodarki specjalności, Dydaktyka i działania wynikające z zaangażowania pracodawców w realizację projektu. Włączenie pracodawców do procesu dydaktycznego pozwoli udoskonalić programy kształcenia i podniesie atrakcyjność kierunku. Oferta kształcenia będzie dostosowana do wymogów rynku pracy. Projekt jest zgodny z Regionalną Strategią Innowacji woj. lubelskiego. Selektywny model rozwoju oparty jest na inteligentnych specjalizacjach rozumianych jako rozwój tych obszarów działalności badawczo-rozwojowej i innowacyjnej, które wzmacniają endogeniczne potencjały rozwojowe regionu. Jedną z nich jest informatyka. Jest to tzw. specjalizacja wspomagająca. Data science, data mining, analiza big data oraz business intelligence to kompetencje przynależne dziedzinie informatyki, dla uzyskania dodatkowej wartości praktycznej i aplikacyjnej w ramach projektu skonfrontowane z obszarem nauk społecznych i finansami przedsiębiorstwa. (Polish)
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    Identifiers

    Polish Kohesio ID
    POWR.03.01.00-00-N041/16
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