Application and use of information and communication technologies (ICTs) across different sectors is placing new demands on higher education, requesting significant changes in the approach to ICR education and learning outcomes in order to match the contemporary digital age and its rapid evolution. The role of higher education is to equip the student population (women especially) with skills in Data Science (DS) and Artificial Intelligence (AI) in order to facilitate not only their further educational careers, but also they employment after the study. As it is shown in the European Commission report on "ICT for Work: Digital Skills in the Workplace", digital skills are necessary in 93% of EU workplaces and are not only required for jobs in the ICT sector. This means that both education and labour market outside the ICT sector, require digital knowledge and skill in order to perform their regular tasks. Additionally, as European parliament published in its report from, information and communication technologies is a sector where women are under-represented and earn less than men. Women are not only less likely to take up studies in this field and but are also much less represented as a work force having skills in this domain for any other job type and position, especially in Data Science and Artificial Intelligence as ones of the fastest developing areas in the STEM field. This is why this project aims to develop short-cycle courses in the areas of Data Science and Artificial Intelligence for students of their last study year or recent graduates in order to bridge the existing challenge. In order to address this objective properly, this project will map and report on the state of the art in the area of DS/AI skills and competencies among students and recent graduates with a particular focus on women. An in-depth analysis will be to provide the full insight into the existing challenges and give the inputs for the development and implementation of the short-cycle courses. Based on the findings of the in-depth analysis, set of DS/AI courses will be developed to fill in the gap between current know-how and skills and requirements for DS/AI skills and knowledge over different sectors. Developed short-cycle courses will be piloted at participating universities, focusing on areas of Data Science, Machine learning, Virtual neural networks, Big Data Analytics, Internet of Things, Bioinformatics, Business Intelligence, Decision Making. In this way, the project will enable students and recent graduates with much needed DS/AI skills that can be applied at their further pursuit of studies and also career in STEM field. Women in particular need a boost in their academic journey, since they are underrepresented in the field of STEM.
By innovating the offer of courses at five partner higher education institutions, the project seeks to build the capacity of students and graduates (women in particular) to continue their education or pursue their business careers in the fields that are not DS/AI sector but require certain DS/AI skills to perform everyday tasks. In that way, the institutions will have a new generation of students who can, e.g. enroll their Master or PhD studies, without being hampered or left behind due to the lack of digital skills. The main objective will be achieved through the set of specific objectives, such as: Specific objective 1: to map and report on the state of the art in the area of DS/AI skills and competencies among students and recent graduates with a particular focus on women. An in-depth analysis will be conducted by all universities to obtain the latest data on the labour market. Specific objective 2: to jointly single out and develop DS/AI courses that would best suit the market needs of all partners in the consortium. Specific objective 3: to teach courses to bridge the gap between formal education skills and DS/AI-related competencies required for contemporary business practices
In order to achieve the set of objectives defined here, the Consortium defined the three activities/results to be developed throughout the project, in such a way that each objective correspond to one result planned in this project. At the beginning of the project, all project partners will conduct an in-depth analysis of the specific requirement for DS/AI skills at their institution in order to provide answers to the questions such as: what are the careers that require DS/AI skills, what DS/AI skills are required, what are the open positions on the labor market, what profile of experts are required, how many women are pursuing careers in STEM area, at what level women are using DS/AI knowledge in their studies, etc. Based on the findings of the analysis, project partners will develop the short-cycle courses to equip the students with DS/AI skills necessary for better studies at next education levels (master and PhD) that will lead to better education and creation of highly skilled work force. The program will cover a variety of topics (challenges) such as data science, machine learning, virtual neural networks, big data analytics, internet of things, bioinformatics, business intelligence and decision making which have a very broad application in HE, even in areas outside of STEM, and also on the labor market. The program will include also the necessary elements such as course objective, expected results, course format, materials, syllabus, course schedule, target groups, lecturers, joint certificates, reviews and feedback after the course, etc.
The project will be implemented around three main parts designed as separate project results. PROJECT RESULT 1 (PR1) – Report on in-depth analysis of the state-of-the-art in the area of DS and AI In-depth analysis will be conducted by all universities to obtain the latest data on DS/AI skills and competencies of students and recent graduates who wish to develop their careers in STEM, with particular emphasis on women. This analysis should provide information about work positions in STEM that require DS/AI skills, currently sought positions in these areas on the labour market and map STEM professional profiles where women are less included. The report primarily aims to provide the initial fact-based inputs for the development of DS and AI courses at participating universities. PROJECT RESULT 2 (PR2) – DS/AI courses developed The DS/AI courses will be designed with the aim to equip students and graduates, especially women, with DS/AI skills necessary for career in STEM-related disciplines. The DS/AI courses will cover different topics (challenges) based on the needs identified in PR1. Based on the experience and lessons learned from in PR2, it will be updated/improved by the end of the project. PROJECT RESULT 3 (PR3) – DS/AI courses realisation This phase refers to the realization of developed DS/AI courses for the first time in a real-world setting. The main target group of the will be final-year students and recent graduates, with the majority of female participants that want to pursue career in STEM. Realisation of courses in practice will show the advantages and disadvantages of the developed courses and, accordingly, provide inputs for the PR2 update. Once PR2 is finalized (improved), developed courses can be fully applied at any institution and for any target group.
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