appliedAI Institute for Europe

Build AI knowledge at your own pace, from foundational concepts to practical workplace applications and specialized topics.

Build practical AI skills and apply trustworthy AI practices through expert-led learning on AI use, engineering, governance, and regulation.

Find AI research, practical tools, and educational materials in one collection, with filters to explore resources by topic, language, and type.

Use tested machine learning software, libraries, and algorithm implementations to support research and practical work.

Help organizations identify AI skill needs, assess current capabilities, and build targeted learning pathways for responsible AI adoption.

Use real-world AI examples and EU AI Act classifications to support risk assessment, regulatory alignment, and research.

Helps decision-makers understand EU AI Act compliance steps, see what comes next, and discuss requirements using a shared visual reference.

Help decision-makers prepare for plausible AI futures by comparing advancement scenarios and examining their potential effects across key domains.

Connect with AI developers, exchange knowledge, showcase work, and organize meetups while contributing to trustworthy AI innovation.

Explore Germany’s AI startup ecosystem, track its development, and find potential AI partners through a searchable, categorized database.

AI learning courses

A collection of AI courses and guided training for learners looking to build foundational knowledge or deepen expertise. The offerings include free, self-paced online courses and on-demand courses covering topics such as AI fundamentals, machine learning, MLOps, anomaly detection, AI literacy, and AI regulation. Course formats include video lessons, interactive activities, and knowledge checks, with practical examples and workbooks in some courses.

• Learn AI At Your Own Pace
  Access free online learning and progress flexibly through course material, with interactive activities and questions to review your knowledge.
• Study Practical AI Topics On Demand
  Choose from on-demand learning on regulatory requirements, responsible AI use, and ChatGPT in the workplace.
• Explore AI From Fundamentals To Specialties
  Build knowledge across a range of subjects, from foundational AI concepts to specialist technical and regulatory topics.
• Apply AI Learning To Real Use Cases
  Use practical examples and workbooks to explore AI applications, including potential use cases tailored to a learner’s business.
• Learn With Experienced AI Experts
  Join guided online learning led by AI experts experienced in the relevant subject areas.
• Reuse And Adapt Course Materials
  For courses whose materials are provided under the stated Creative Commons license, organizations can share and adapt the content with attribution. Available SCORM, editable Articulate Storyline, and MP4 files support integration into learning platforms and educational websites.

Workshops and training

The appliedAI Institute for Europe offers guided online courses, workshops, and training led by AI experts experienced in their subject areas. Sessions address practical AI use and technical implementation as well as regulatory topics, including AI Act compliance, AI standards, engineering practices, generative and agentic AI governance, and the intersection of the AI Act and GDPR. Training uses practical examples and provides guidance for applying requirements, assessing AI use cases, and taking compliance steps.

Category: AI Training Services

• Apply AI Act Requirements In Practice
  Build a structured understanding of how to identify applicable AI Act requirements, translate them into organizational actions, and document conformity.
• Learn From Experienced AI Experts
  Receive guided instruction from AI experts experienced in the relevant subject areas, including trustworthy AI, AI regulation, and engineering.
• Connect Standards And Engineering To Compliance
  Learn how AI standards, technical practices, and engineering workflows can support compliance, including the use of suitable evidence and tools.
• Understand Governance For Generative AI
  Identify relevant regulatory responsibilities for generative and agentic AI systems and assess governance resources and practices suited to an organization.
• Navigate AI And Data Protection At Work
  Learn to assess everyday AI use involving personal data and recognize situations where organizational data protection support may be needed.
• Get More From Large Language Models
  Explore practical prompting techniques for making more effective use of large language models.
• Choose Guided Online Or Event-Based Learning
  Access guided online courses as well as scheduled workshops and training sessions with published event information and registration links.

AI resources

AI resources is an online collection of more than 200 AI-related resources, including software projects, research papers, articles, summaries, data, publications, infographics, posters, and databases. Visitors can browse resources by topic, language, and type. The collection includes practical software and tools, research and educational materials, and resources on areas such as machine learning, MLOps, data competence, and AI regulation.

• Explore 200+ AI Resources
  Browse a large collection of AI materials in one place, including software projects, research, articles, summaries, and data.
• Browse Multiple Resource Formats
  Choose from different kinds of materials, from software and documents to blogs, paper summaries, databases, posters, and infographics.
• Find Resources By Topic
  Narrow the collection by subject areas such as machine learning, MLOps or infrastructure, data competence, and AI regulation.
• Filter Resources By Type
  Use type filters to find materials such as documents, blogs, paper summaries, databases, posters, infographics, or software.
• Filter Resources By Language
  Choose English or German resources using the collection's language filter.

AI tools and software

A collection of software developed by appliedAI Institute for Europe to support researchers and practitioners. It includes high-level machine learning libraries and reference implementations of new algorithms. The institute tests and evaluates new methods and provides robust, well-documented, thoroughly tested implementations that go beyond what is typically found in academic papers. The collection also includes the open-source lakeFS-spec Python library, which simplifies file access and versioning in a lakeFS Data Lake.

• Use Robust, Documented, And Tested Implementations
  Work with implementations produced after method testing and evaluation. The institute describes these implementations as robust, well documented, and thoroughly tested.
• Access High-Level Machine Learning Libraries
  Use high-level machine learning libraries developed to support research and practical work.
• Use New Algorithms Through Reference Implementations
  Explore new algorithms through reference implementations provided by the institute.
• Simplify lakeFS Data Lake File Access
  Use the open-source lakeFS-spec Python library to simplify file access and versioning in a lakeFS Data Lake, with a workflow described as being as easy as working in a local file system.

AI Skills Framework

The AI Skills Framework is a practical structure that translates AI competence into concrete, assessable skills. It brings technical, organizational, and governance skills together for professionals who use, integrate, develop, or shape AI. Organizations can use it to identify required capabilities, assess current skills, compare skill profiles, and build targeted learning pathways for responsible AI adoption. Its components are organized into five competency levels and can be viewed by purpose, domain, role, or AI system.

• Define And Assess Practical AI Skills
  Give organizations concrete skills to assess and develop, rather than relying only on broad descriptions of AI competence.
• Assess Capabilities And Build Learning Pathways
  Help organizations understand current skills in relation to needed capabilities and use that assessment to structure relevant learning pathways.
• Map Skills Across Four AI Interactions
  Relate skill development to whether professionals use, integrate, develop, or shape AI, supporting different entry points for workforce skills development.
• Cover Technical, Organizational And Governance Skills
  Bring together capabilities across technical work, organizational implementation, and AI governance in a single skills structure.
• Track Progress Across Five Competency Levels
  Show how a skill progresses from initial awareness to independent, flexible application and mastery, making development stages clearer.
• View Skills By Purpose, Domain, Role Or System
  Use different views of the skill components to identify competency patterns, compare roles, and tailor skills development to specific domains or AI systems.
• Ground Skills In Research And Practical Testing
  Base the framework on applied research, expert review, and practical tests with partner organizations.
• Connect AI Skills With Essential Work Competencies
  Make visible the role of collaboration, communication, problem-solving, and critical thinking in applying AI-related skills effectively.

Risk Classification Database

An open, free database of real-world AI use cases classified under the EU AI Act. It provides risk classifications and transparency-obligation information, with filters for risk class, transparency status, and business function. The database is intended as an empirical reference for AI system classification, a resource for alignment between providers and authorities, and a data source for academic research. Its scope is primarily industrial, with a focus on Germany and the EU; the dataset page notes that some classifications may be unclear or outdated.

• Compare EU AI Act Risk Levels
  Consult classifications across the listed risk categories to help assess how AI use cases are categorized under the EU AI Act.
• Explore Practical AI Use Cases
  Review concrete AI application examples alongside their listed business function and regulatory classifications, with links to more information about individual cases.
• Review Transparency-Obligation Status
  Check the transparency-obligation status associated with listed use cases, including whether an obligation is applicable, not applicable, unclear, or has not been checked.
• Access The Database For Free
  Consult the open database without charge as a reference when examining AI system classifications.
• Support Alignment And Research
  Use the database as a shared reference for provider-authority alignment and as a data source for academic research related to the EU AI Act.
• Find Use Cases By Business Function
  Narrow the database to AI use cases associated with specific business functions, making it easier to consult examples relevant to an organizational area.
• Download Details And Statistics
  Access a downloadable document with details and descriptive statistics about the database.

EU AI Act Compliance Journey

The EU AI Act Compliance Journey is an infographic and flowchart that maps the phases and decision points involved in navigating the EU AI Act. It helps users understand the regulation at a glance and follow the steps AI projects need to consider, from risk classification to market entry and compliant rollout. Designed especially for people beginning to learn about the AI Act, it provides context for requirements and a shared reference for discussion. The Journey is presented as a draft and is available to download as a PDF.

• Visualize Compliance Phases And Decisions
  See the compliance journey's phases and decision points in one flowchart to orient yourself within the EU AI Act.
• Follow Steps From Classification To Rollout
  Use the sequence of steps to navigate the EU AI Act from risk classification through to compliant deployment of AI systems.
• Understand The Act At A Glance
  Get an accessible overview of the regulation's overall structure and journey without having to begin with a detailed reading of every provision.
• Become Familiar With The Act Faster
  Use the map to guide focused reading and build familiarity with the AI Act more quickly.
• Ask Better-Informed Questions
  Understand the context around requirements so discussions and questions can be more focused.
• Align Discussions Around A Shared Map
  Use the same visual reference when discussing the EU AI Act's phases and decision points with others.
• Download The Journey As A PDF
  Access the Journey in a downloadable PDF format for reference.
• Contribute Feedback To Ongoing Development
  Provide critical feedback on the draft to help inform the Journey's continued development.

Preparing for the Age of AI

Preparing for the Age of AI is a living outlook for decision-makers, offering a structured framework for navigating AI advancement over the next 36 months. Rather than making a single prediction, it compares three plausible capability-progress projections and assesses how they could affect ten key domains. The outlook combines AI-based signal monitoring and news identification with human expert review of its summaries and projection assessments. Visitors can explore the framework online or download the full study.

• Prepare Across Plausible AI Futures
  Use a defined 36-month horizon to consider possible AI developments and prepare for more than one potential future.
• Compare Three AI Progress Scenarios
  Explore three distinct capability-progress trajectories, along with the outlook’s assessment of their likelihood over the next 36 months.
• Assess Potential Impacts Across Key Domains
  Compare how different AI progress scenarios could affect important areas of society and the economy, including work, industry, science, and security.
• Combine AI Monitoring With Expert Review
  Use outlook content informed by AI-based monitoring and news identification, with summaries and projection assessments reviewed and supervised by human experts.
• Explore Scenarios And Download The Study
  Access the framework online to explore its projections, or download the full study for further review.

appliedAI Developers

appliedAI Developers brings together AI developers from companies, universities, and nonprofit organizations to advance trustworthy AI innovation. The community supports monthly meetups, networking, and knowledge sharing, with meetups in Heilbronn and Munich. Members can also organize their own meetups and showcase their work.

• Connect With Diverse AI Developers
  Meet AI developers from companies, universities, and nonprofit organizations through a community focused on trustworthy AI innovation.
• Meet Developers In Person
  Join recurring developer meetups in Heilbronn and Munich to connect with members of the community.
• Build Developer Connections
  Connect with AI developers from different types of organizations through the community's networking activities.
• Exchange AI Knowledge
  Share and learn knowledge with AI developers from companies, universities, and nonprofit organizations.
• Host Your Own Meetups
  Members can organize their own meetups to bring developers together around their interests and work.
• Showcase Your Work
  Present your work to other AI developers in the community.

AI Startup Landscape (Germany)

The AI Startup Landscape is an annually published analysis and searchable database of Germany’s AI startup ecosystem. It presents startups by categories such as industry, technology type, AI capabilities, and enterprise function, with company descriptions, regional information, and ecosystem insights. Users can search by company name or keywords, review secondary categories, and visit startup websites. The 2025 edition lists 935 startups and reports 36% year-on-year growth, alongside analysis of the ecosystem’s development. The landscape is designed to make AI startups more visible, advance AI adoption, and help businesses, SMEs, and public institutions find potential AI partners.

• Find Potential AI Partners
  Search the database to identify German AI startups by name or keywords, review their descriptions, and follow links to their websites.
• Track Ecosystem Trends
  Use reported startup counts, growth, regional distribution, technology, and funding information to understand developments in Germany’s AI startup ecosystem.
• Discover Trusted AI Partners
  Explore startup profiles to identify potential AI partners for businesses, SMEs, and public institutions, supporting collaboration between startups and established organizations.
• Compare Startups By Category
  Browse startups using the landscape’s categories and review additional company details and secondary classifications in the table.
• Review Expert-Assessed Startups
  Rely on a selection process that combines analyst screening, defined assessment criteria, and expert review to evaluate startups for inclusion.
• Follow Annual Ecosystem Updates
  Compare yearly editions to follow changes in the German AI startup landscape and its reported ecosystem trends.