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ARISA Learning Materials

ARISA Learning Materials (2025 update)
These learning materials are the final, updated version of the ARISA training resources developed throughout the project. They have been refined following extensive testing and evaluation during the pilot phase, ensuring they reflect both learner feedback and the practical experience of trainers.
The updated materials incorporate improvements based on evaluation reports, assessment results, focus groups, questionnaires and learning analytics. As a result, both the content and teaching methodology have been enhanced to provide a more engaging, effective and relevant learning experience.
Designed for vocational education and training (VET) providers, higher education institutions, trainers and other organisations delivering AI skills training, these resources support the development of high-quality AI education aligned with the needs of today’s labour market.
Data Analyst EQF 6 – BCS Koolitus
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- Material 3
- Material 4
- Material 5
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- Material 7
- Material 8
- Material 9
- Material 10
- Material 11
Machine Learning Engineer EQF 7 – Budapest University of Technology and Economics
Deep Learning – Basics
Presentations
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- Material 2: Presentation
- Material 3: Presentation
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- Material 9: Presentation
Practice materials
- Regression Modeling
- Image Classification with Multi-Layer Perceptron on CIFAR-10
- Introduction to Deep Learning-Based Image Classification and Evaluation
- Inference with a Pretrained Neural Network
- Transfer Learning
- Text-Classification with Deep Learning
- Character-based Text Generation with LSTMs
- Anomaly Detection with Autoencoders (Tabular Data)
- Anomaly Detection with Variational Autoencoders (VAE)
- TensorBoard
Deeps Learning – Advanced
Presentations
- Material 1: Presentation
- Material 2: Presentation
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- Material 10: Presentation
Practice materials
- Basics: Material 1; Material 2; Material 3
- Hyperopt: Material 1; Material 2
- Regression
- Computer Vision
- Advanced Sequence Modeling: Material 1; Material 2
- Graph Neural Networks: Material 1; Material 2; Material 3; Material 4
- GANS: Material 1; Material 2
Applied AI
Presentations
- Material 1: Presentation
- Material 2: Presentation
- Material 3: Presentation
- Material 4: Presentation
- Material 5: Presentation
- Material 6: Presentation
- Material 7: Presentation
- Material 8: Presentation
- Material 9: Presentation
- Material 10: Presentation
Practice materials
AI Advisor EQF 6 – Skillsoft Global Knowledge France
- Guardrails & governance – GDPR
- AI Fundamentals
- Understanding the AI landscape
- Enhancing work with AI
- Strategy, transformation & implementation
Decision maker EQF 6 – HU University of Applied Sciences Utrecht
- Overview of AI fundamentals
- Fields of AI application
- Ethics of AI
- Regulatory landscape
- AI and business strategy
Policymaker EQF 6 – HU University of Applied Sciences Utrecht
- Machine learning
- Deep learning
- Ethical compass in digitisation
- Fairness in AI
- Responsible data usage
- Governmental building blocks
- Legality in AI regulations
- AI Act
Decision maker EQF 7 – Mylia
Machine Learning Engineer EQF 6 – Kharkiv National University of Radio Electronics
Data Analyst EQF6 – University of Ljubljana
Decision Maker and Policymaker EQF6 – University of Ljubljana
Data Scientist EQF 6 – UNIR Universidad Internacional de la Rioja
Machine Learning Supervised
- Material 1
- Material 2
- Material 3
- Material 4
- Material 5
- Material 6
- Material 7
- Material 8
- Material 9
- Material 10
Machine Learning Unsupervised
Neural Networks
Human-Centered AI
Machine Learning Engineer EQF 7 – Warsaw School of Computer Science
Machine Learning Foundations
- Introduction
- Material 1
- Material 2
- Material 3
- Material 4
- Material 5
- Material 6
- Material 7
- Material 8
- Bonus Materials
Data Science
Deep Learning
GenAI
MLOps
AI Apps
AI Law and Ethics
