Pioneering
ML Excellence
Across Europe
Founded by former Google DeepMind researchers, we bridge the gap between cutting-edge AI research and production-ready engineering skills
Back to HomeOur Story & Mission
From research breakthroughs to production excellence - the journey that shaped European ML education
The Genesis
In the autumn of 2021, three former researchers from Google DeepMind's Zurich lab gathered at ETH's main building, discussing a persistent challenge: the growing disconnect between groundbreaking AI research and the practical skills needed to deploy these innovations in real-world applications.
Having witnessed firsthand how academic ML programs produced brilliant theorists who struggled with production systems, and how bootcamps created coders without deep understanding of algorithmic foundations, we recognized an urgent need for a new approach to ML education.
By January 2022, we had assembled a founding team of former researchers from DeepMind, Meta AI, and senior engineers from Spotify, Netflix, and leading Swiss fintech companies. Our shared vision: create the world's most comprehensive ML engineering education specifically designed for European tech ecosystem's unique challenges.
Evolution & Growth
Since our launch in February 2022, we've continuously evolved our curriculum based on real feedback from industry partners and graduate career progression. Our advisory board includes ML leads from major European companies who help ensure our training remains aligned with current industry demands.
What started as a single 16-week program has grown into three specialized tracks, each designed for different career stages and goals. We've maintained our commitment to small cohort sizes, ensuring every student receives personalized attention and mentorship from our experienced instructor team.
Our expansion across the DACH region reflects the growing demand for practical ML engineering skills. With partnerships established at leading universities and direct recruitment relationships with 50+ companies, we've created a comprehensive ecosystem supporting European AI talent development from education through career advancement.
Our Evidence-Based Methodology
Professional standards rooted in cognitive science and validated through real-world outcomes
Project-First Learning
Students build real ML systems from day one, developing intuitive understanding before diving into theoretical complexities. Each project mimics actual industry challenges.
Spaced Repetition
Key concepts are revisited at strategically timed intervals, ensuring long-term retention and progressive skill building aligned with memory consolidation research.
Deliberate Practice
Focused practice on specific skills with immediate feedback, progressive difficulty adjustment, and continuous performance monitoring based on expert performance research.
Research-Backed Results
Measurable Impact Across Europe
Real results driving AI transformation in European enterprises and startups
Industry Transformation
Swiss Financial Services
42 graduates now work at major Swiss banks and fintech companies, implementing fraud detection systems processing €2.3B daily transactions with 99.7% accuracy.
German Automotive AI
38 alumni contribute to autonomous driving systems at BMW, Mercedes, and Volkswagen, working on computer vision models trained on 50M+ European road scenarios.
Austrian Tech Startups
29 graduates have founded or joined early-stage AI companies, collectively raising €47M in seed funding and creating 150+ new ML engineering positions.
Career Progression
+156%Average salary increase within first year post-graduation
Technical Leadership
73%Graduates promoted to senior or lead positions within 18 months
Innovation Impact
€2.1BCombined value of ML systems built by our graduates since 2022
Geographic Reach
Our Leadership Team
World-class researchers and engineers dedicated to advancing ML education excellence
Dr. Kira Thalgauer
Co-Founder & CEO
Former DeepMind Research Scientist specializing in reinforcement learning and multi-agent systems. Led breakthrough research on scalable RL algorithms published in Nature Machine Intelligence. PhD from ETH Zurich in Computational Intelligence.
Magnus Eriksson
Co-Founder & CTO
Former Meta AI Senior Engineer who architected production ML systems serving 3B+ users. Expert in distributed training, model optimization, and MLOps infrastructure. MS Computer Science from KTH Stockholm.
Dr. Amelie Dubois
Head of Curriculum
Former EPFL Professor of Machine Learning and Spotify Senior ML Engineer. Pioneer in curriculum design for technical education with 15+ years experience. PhD in Educational Psychology from Sorbonne, specializing in accelerated learning.
Quality Standards & Safety Protocols
Comprehensive approach ensuring excellence, security, and ethical AI practices
Academic Excellence
Rigorous Assessment Framework
Multi-stage evaluation process including practical projects, technical interviews, and peer code reviews ensuring mastery of core concepts.
Industry-Validated Curriculum
Quarterly reviews with enterprise ML teams ensure our content reflects current industry needs and emerging technology trends.
Continuous Improvement
Data-driven optimization of teaching methods based on learning outcomes, employment success, and long-term career tracking.
Security & Privacy
GDPR Compliance
Full compliance with European data protection regulations including encrypted storage, right to deletion, and transparent data usage policies.
Secure Infrastructure
Swiss-hosted infrastructure with end-to-end encryption, multi-factor authentication, and regular security audits by independent third parties.
Ethical AI Training
Mandatory modules on AI ethics, bias detection, and responsible deployment practices integrated throughout all program tracks.
ISO 21001 Certified
Educational organizations management system certification
SOC 2 Type II
Security, availability, and confidentiality compliance verified
Partnership Verified
Official partnerships with Google Cloud, AWS, and Azure for ML
Company Values & Expertise
AtCheckenui, our core values of excellence, innovation, and practical impact guide every aspect of our educational mission. We believe that world-class machine learning education should be accessible, rigorous, and immediately applicable to real-world challenges faced by European enterprises and startups.
Our expertise spans the complete spectrum of modern ML engineering: from foundational mathematics and statistics through advanced deep learning architectures, distributed computing, and production deployment strategies. We maintain active research collaborations with leading European universities while ensuring our curriculum reflects the latest industry best practices from companies processing petabytes of data daily.
What distinguishes our approach is the integration of cognitive science research into our pedagogical methodology. We don't just teach machine learning algorithms—we teach how to learn and apply complex technical concepts efficiently, creating graduates who can adapt and excel as the field continues its rapid evolution. Our commitment to measurable outcomes ensures that every program element contributes directly to student success in their post-graduation careers.
Since our founding in 2022, we've consistently delivered on our promise to bridge the gap between academic research and production reality. Our graduates don't just understand TensorFlow syntax or PyTorch operations—they architect systems that scale to millions of users, design experiments that drive business decisions, and implement ML solutions that create tangible value for European organizations across finance, automotive, healthcare, and emerging technology sectors.
Join the Future of ML Engineering
Experience the methodology that's transforming careers across Europe. Next cohort begins August 12, 2025.