Master Machine Learning
Engineering
Transform your career with comprehensive ML courses designed for the DACH region. From Python fundamentals to production systems at scale.
Trusted by Leading Tech Companies
Our graduates work at top companies across Switzerland, Austria, and Germany
Certified Excellence
Google ML certification preparation with 98% pass rate since July 2025
Industry Experience
Instructors from FAANG companies with 8+ years production ML experience
Proven Track Record
3 years of successful placements in Swiss fintech and German automotive AI
Pioneering ML Education in Europe
Founded in early 2022 by former Google DeepMind and ETH Zurich researchers,Checkenui emerged from a simple observation: the European tech ecosystem needed world-class machine learning talent, but traditional education wasn't keeping pace with industry demands.
Our mission centers on bridging the gap between academic theory and production reality. Every course module reflects real challenges our instructors faced while scaling ML systems at companies processing billions of daily predictions. We don't just teach algorithms—we teach the engineering discipline that makes ML work in production.
Since July 2022, we've maintained an unwavering commitment to practical excellence. Our graduates don't just understand TensorFlow syntax; they architect systems that serve millions of users, debug distributed training failures, and design A/B testing frameworks that drive business decisions.
What sets us apart is our relentless focus on the DACH region's unique technical landscape. From Swiss financial regulations affecting model deployment to German automotive safety standards for AI systems, our curriculum addresses the real regulatory and technical challenges you'll face in your career.
Excellence
Production-grade standards in every project and assessment
Innovation
Cutting-edge techniques from latest research and industry practice
Impact
Graduates driving AI transformation across European enterprises
Professional ML Engineering Programs
Comprehensive training paths designed for different career stages and goals
ML Engineering Foundations
Comprehensive introduction to ML engineering covering Python, TensorFlow/PyTorch, and MLOps basics with hands-on computer vision and NLP projects.
- Python for ML & Data Processing
- TensorFlow & PyTorch Fundamentals
- AWS/GCP Integration Workshops
- Google ML Certification Prep
- Weekly Code Reviews
Production ML Systems
Advanced program focusing on scalable ML architecture, distributed training, and real-time inference systems for enterprise environments.
- Scalable ML Architecture Design
- Kubernetes for ML Deployment
- Apache Spark & Distributed Training
- A/B Testing Frameworks
- Real-time Inference Systems
Career Transformation
Immersive bootcamp with guaranteed job placement in DACH region. Includes mentorship, capstone projects, and direct recruitment pipeline.
- Guaranteed Job Placement
- 3 Industry Capstone Projects
- FAANG Engineer Mentorship
- Mock System Design Interviews
- Direct Recruitment Pipeline
Why Choose Our ML Engineering Programs
Natural, evidence-based learning approach with personalized solutions for your career goals
Natural Learning Progression
Our curriculum follows the natural progression of how expert ML engineers actually develop their skills. Starting with hands-on projects from day one, you'll build intuition through practice before diving into complex theory.
- Project-first learning methodology
- Gradual complexity increase
- Real-world problem solving focus
Personalized Career Solutions
Every student receives a customized learning path based on their background, career goals, and learning style. Our adaptive curriculum ensures optimal progress regardless of your starting point.
- Individual skill assessment and gap analysis
- Customized project portfolios
- Targeted career placement strategy
Ready to Transform Your Career?
Join the next cohort starting in August 2025. Limited seats available for our most popular programs.
Frequently Asked Questions
Everything you need to know about our ML engineering programs
What background do I need to start the ML Engineering program?
Our Foundation program requires basic programming experience (any language) and undergraduate-level mathematics. For Production Systems and Career Transformation tracks, we recommend 1-2 years of software development experience. We provide comprehensive pre-program assessments to ensure you're placed in the right track for your skill level.
How does the job placement guarantee work?
Our Career Transformation program includes a placement guarantee: if you successfully complete all requirements and actively participate in our placement process, we guarantee you'll receive a qualifying job offer within 6 months of graduation, or we'll provide full tuition refund. Qualifying offers must be ML engineering roles with salaries above €65,000 EUR in the DACH region.
What's the typical timeline from start to employment?
Foundation program graduates typically find positions within 2-4 months after completion. Production Systems students often secure roles during the program due to our industry partnerships. Career Transformation students begin interviewing in week 20, with most receiving offers before graduation. Our average time-to-employment is 6 weeks post-graduation across all programs.
Are payment plans available for the programs?
Yes, we offer several payment options: upfront payment with 10% early bird discount (until July 30, 2025), interest-free installments over program duration, and Income Share Agreements (ISA) for Career Transformation students. ISA participants pay nothing upfront and contribute 15% of salary for 24 months after securing employment above €60,000 EUR annually.
How do you ensure student privacy and data protection?
We maintain strict GDPR compliance with encrypted storage of all personal data, limited access protocols, and transparent data usage policies. Student project work remains confidential, and we never share personal information with employers without explicit consent. Our Swiss-based infrastructure ensures additional privacy protections under Swiss Federal Data Protection Act standards.
Can I study part-time while working full-time?
Our Foundation and Production Systems programs offer evening schedules designed for working professionals. Classes run Tuesday/Thursday 7-10 PM CET with weekend project sessions. Career Transformation requires full-time commitment due to intensive capstone projects and interview preparation. We recommend 15-20 hours weekly for part-time programs and 40+ hours for full-time track.
Ready to Begin Your ML Journey?
Get personalized program recommendations and early access to our next cohort