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Good practice Imported

AI For All — EIT-Funded Deep-Tech Microcredentials via Vilnius Business College

Lithuania · Vilnius · See the Lithuania profile · See the Vilnius profile

Evidence: Descriptive / self-reported Top 89% 27/100 · Ask Evidence Copilot about this practice

Vilnius Business College, with Warsaw School of Computer Science and Lucerne University, won EIT Deep Tech Talent funding (1 of 15 chosen from 97 proposals) for "AI For All," building free, no-prerequisite AI microcredentials focused on female participation.

15 of 97 proposals
EIT proposals approved (selection round)
AI For All — EIT-Funded Deep-Tech Microcredentials via Vilnius Business College

Details

Maturity
Pilot
Promoter
Vilnius Business College (EIT Deep Tech Talent Initiative — "AI For All")
Period
2024–2026
Region (NUTS)
LT01
Keywords
higher education, deep-tech skills, gender equity in STEM, micro-credentials

Context

'AI for All: Tapping into Deep Tech Through a Diverse Training Program' is a project of Warsaw School of Computer Science (coordinator, Poland), Vilnius Business College (Lithuania) and Lucerne University of Applied Sciences and Arts (HSLU, Switzerland), funded under the EIT Deep Tech Talent Initiative. The consortium was one of 15 proposals approved out of 97 submitted.

Objectives

Increase the accessibility of AI tools to academic communities in the three countries through interactive lecture modules, with a stated focus on encouraging female participation in AI study.

Activities

The project's output, HSLU's 'Deep Tech Microcredentials,' launched 1 December 2025 as free, self-paced, English-language online courses requiring no prior AI background, spanning tracks such as medical AI and data-driven engineering; originally designed for students at Warsaw School of Computer Science and Vilnius Business College, they are now available more broadly.

Conclusions

As a programme launched within the last reporting period, no enrolment, completion or learning-outcome data has yet been published; this entry reflects verified programme design, competitive-selection and access facts rather than measured impact.

Implementation
Indicative cost
Medium (€50k–€500k) — No cost figure stated; medium band is a conservative inferred estimate for a three-country academic consortium developing multiple microcredential tracks.
Time to results
Medium (1–3 years) — Project ran 2024-2026; the resulting Deep Tech Microcredentials launched 1 December 2025.
Staffing & skills
Warsaw School of Computer Science (coordinator), Vilnius Business College, Lucerne University of Applied Sciences and Arts (HSLU)

Conditions for success

  • Competitive EIT selection (1 of 15 from 97 proposals) provides external quality signal
  • Free, no-prerequisite, self-paced design lowers access barriers
  • Explicit focus on encouraging female participation in AI

Common failure modes

  • No enrolment, completion or learning-outcome data published yet, as the microcredentials only launched in December 2025

Where it fits

Governance type
three-country academic consortium under an EU-backed initiative
Scale
multi-country (Poland, Lithuania, Switzerland)
Income level
high-income

Commonly funded by

European Urban Initiative

Indicative funding routes for practices of this type — always check each programme's current calls and eligibility rules.

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Data sources

Where this practice's information was retrieved from, and when.

Attachments

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