ARISA Newsletter: December 2024

ARISA has released a suite of new resources designed to boost AI education and training across Europe. These comprehensive materials aim to bridge the AI skills gap by supporting education providers, governments, industry leaders, and training representatives in skilling, reskilling, and upskilling individuals into AI-related roles.

Core Curricula framework provides a practical guide for designing and structuring educational programmes tailored to the needs of AI-related roles. It covers both technical profiles, including Data Analyst, Data Scientist, Machine Learning Engineer, and NLP Engineer, and non-technical profiles, such as Policymakers, AI Advisors and Decision Makers.

Learning programmes training materials offer holistic resources that cater to the specific needs of the identified profiles. Featuring detailed instructions, practical examples, and hands-on activities, they are designed to empower learners to thrive in AI-driven roles.

European mobility programme overview of existing EU mobility opportunities for AI education, helping institutions foster cross-border collaboration and knowledge sharing.

Work-based learning components include guidelines for integrating real-world, hands-on experiences into AI training programmes, ensuring learners gain practical expertise in addition to theoretical knowledge.

BROWSE THE ARISA RESOURCES

INTERESTING READS

AI and Cybersecurity: Addressing risks and opportunities through the ARISA project
As AI continues to transform industries, its adoption into various sectors brings new cybersecurity challenges. Cybersecurity is integrated into the ARISA curricula, equipping participants not only with AI expertise but also with the vital knowledge to mitigate security risks posed by AI advancements.

AI and the Future of Learning: Key Factors for Success (Webinar recording)
On 19th of September 2024, ARISA organised the AI and the Future of Learning: Key Factors for Success webinar, bringing together educators, industry experts, and members of the ARISA community to explore the transformative potential of AI in the educational landscape.

Adapting to the AI Era: The Imperative of Skills Development
Data shows that 80% of people globally want to learn more about the use of AI in their work. Yet businesses across Europe are lagging in helping their workforce develop AI skills. To fully use the potential of AI, companies need to focus more on upskilling their employees in this field.

UPDATES CORNER

On 26 November, the AI Skills Alliance partners from across Europe🌍 came together at DIGITALEUROPE’s HQ in Brussels to share updates, celebrate progress, and plan for what’s next.

🎤 Highlights from our sessions:
👉 Partners from the Warsaw School of Computer Science, HU University of Applied Sciences Utrecht, and Budapest University of Technology and Economics gave us insights into their ongoing AI learning programme pilots.
👉 University of Ljubljana introduced their AI self-study course – more details soon!

The agenda also included micro-credentials within the ARISA project and the AI Career Guidance platform, set to launch next year.🔜

We are thrilled to work with such a dynamic team of AI innovators and enthusiasts, building the skills for tomorrow.

✨The ARISA Alliance extends warm wishes for a joyful holiday season and a successful 2025 to all our network members and AI enthusiasts around the globe.✨

MORE FREE RESOURCES

• Quality Label Methodology for AI education programmes
  This Quality Label Methodology serves to outline the framework that will be applied to assess the quality of the programmes/micro-credentials that are developed within the ARISA project.
  The results of the Quality Label Methodology are a transparent Quality Assurance process and a clear path for providers to obtain the ARISA Quality Label.
• ARISA Quality Label General Criteria
  This document serves to present the ARISA General Criteria that are part of the Quality Framework as described in the Quality Label Methodology. Furthermore, it outlines the procedural principles that are the foundation of awarding the ARISA Quality Label.
• ARISA Quality Label Subject-Specific Criteria
  These Subject-Specific Criteria (SSC) are written to complement the General Criteria as part of the ARISA Quality Label Framework. The objective of creating the SSC is to have an instrument – a set of validated, subject-specific standards – to be able to review AI learning programmes within the framework of the ARISA Quality Label.

Join the AI Skills Alliance as an Associated Partner

By becoming an ARISA Associated Partner, your organisation gains access to a vibrant network that fosters knowledge exchange, collaboration, and the collective pursuit of excellence in AI skills development. We offer you the flexibility to choose where to contribute so it aligns better with your organisation’s goals. 

Sounds interesting? Read more about the Associated Partnership opportunity & apply. 

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