
Professional
ML Engineering
Programs
Comprehensive training paths designed for different career stages and goals. From foundations to production systems mastery.
Back to HomeOur Comprehensive Methodology
A systematic approach to ML engineering education that produces industry-ready professionals
Evidence-Based Learning Architecture
Progressive Skill Building
Each program builds systematically from mathematical foundations through production deployment, ensuring no critical knowledge gaps.
Industry Integration
Real-world projects using actual enterprise datasets and production constraints prepare students for immediate workplace impact.
Continuous Assessment
Regular evaluations and feedback cycles ensure mastery before advancement, maintaining high standards throughout the learning journey.
Specialized Training Programs
Three distinct pathways designed for different experience levels and career objectives

ML Engineering Foundations
Comprehensive introduction to ML engineering covering Python, TensorFlow/PyTorch, and MLOps basics with hands-on computer vision and NLP projects.
Core Technologies
- • Python for ML & Data Processing
- • TensorFlow & PyTorch Fundamentals
- • NumPy, Pandas, Scikit-learn
Cloud Platforms
- • AWS/GCP Integration Workshops
- • Model Deployment Basics
- • Cloud Storage & Computing
Certification Prep
- • Google ML Certification Prep
- • Mock Exams & Practice Tests
- • Industry Recognition
Mentorship
- • Weekly Code Reviews
- • 1:1 Expert Sessions
- • Career Guidance

Production ML Systems Specialization
Advanced program focusing on scalable ML architecture, distributed training, and real-time inference systems for enterprise environments.
Architecture Design
- • Scalable ML Architecture
- • Microservices for ML
- • System Design Patterns
Container Orchestration
- • Kubernetes for ML Deployment
- • Docker Containerization
- • Auto-scaling Strategies
Distributed Computing
- • Apache Spark & Distributed Training
- • Multi-GPU Processing
- • Cluster Management
Experimentation
- • A/B Testing Frameworks
- • Statistical Analysis
- • Business Impact Measurement

ML Engineering Career Transformation
Immersive bootcamp with guaranteed job placement in DACH region. Includes mentorship, capstone projects, and direct recruitment pipeline.
Job Guarantee
- • 95% Placement Rate
- • 6-Month Guarantee
- • Salary Floor €65,000
Capstone Projects
- • 3 Industry Projects
- • Real Client Problems
- • Portfolio Development
Expert Mentorship
- • FAANG Engineer Mentors
- • Weekly 1:1 Sessions
- • Career Strategy Planning
Interview Prep
- • Mock System Design Interviews
- • Technical Coding Practice
- • Behavioral Interview Training
Program Comparison & Selection Guide
Compare features and find the perfect program match for your experience level and career goals
Feature | Foundations | Production Systems | Career Transformation |
---|---|---|---|
Program Duration | 14 weeks | 18 weeks | 24 weeks |
Prerequisites | Basic Programming | 1-2 Years Experience | Any Background |
Investment | €3,299 | €5,499 | €9,899 |
Job Placement Support | Career Guidance | Industry Connections | 95% Guarantee |
Capstone Projects | 2 Projects | 4 Projects | 3 Industry Projects |
Mentorship Level | Group Sessions | Bi-weekly 1:1 | Weekly 1:1 FAANG |
Production Systems Focus | |||
Expected Salary Range | €55k - €75k | €70k - €95k | €75k - €120k |
Choose Foundations If
- • New to machine learning
- • Want certification preparation
- • Prefer part-time schedule
- • Budget-conscious approach
- • Seeking career transition
Choose Production If
- • Have programming experience
- • Want scalable systems expertise
- • Target senior engineer roles
- • Enterprise environment focus
- • Advanced technical depth
Choose Transformation If
- • Need guaranteed placement
- • Want comprehensive support
- • Serious career change
- • Maximum salary potential
- • Full-time commitment available
Technical Standards & Protocols
Shared excellence standards ensuring consistent quality across all program tracks
Code Quality Standards
Production-Ready Code
All projects must meet enterprise-level code quality standards including comprehensive testing, documentation, and error handling.
- • 90%+ test coverage requirement
- • PEP 8 compliance for Python
- • Comprehensive docstring documentation
- • Git best practices and version control
Performance Optimization
Focus on efficient algorithms, memory management, and scalable solutions that perform well under production constraints.
- • Sub-second inference requirements
- • Memory-efficient implementations
- • Parallel processing optimization
- • Profiling and bottleneck analysis
Security & Compliance
Data Protection
GDPR-compliant data handling practices with encryption, access controls, and privacy-preserving ML techniques.
- • End-to-end encryption protocols
- • Data anonymization techniques
- • Access logging and audit trails
- • Privacy-preserving ML methods
Model Governance
Comprehensive model lifecycle management including versioning, monitoring, and bias detection for responsible AI deployment.
- • Model versioning and rollback
- • Bias detection and mitigation
- • Explainability requirements
- • Continuous monitoring systems
Industry Certifications & Partnerships
Google Cloud
ML Certification Partner
AWS
Authorized Training Partner
Microsoft Azure
Learning Partner
TensorFlow
Developer Certificate
Professional Technology Stack
Industry-standard tools and infrastructure supporting world-class ML engineering education
Development Environment
- JupyterHub with GPU access
- VS Code with ML extensions
- Docker containerization platform
- Git version control with GitLab
- MLflow experiment tracking
Computing Infrastructure
- NVIDIA A100 GPU clusters
- Kubernetes orchestration platform
- Apache Spark distributed computing
- High-performance storage systems
- Load balancing and auto-scaling
ML & Data Tools
- TensorFlow & PyTorch frameworks
- Weights & Biases monitoring
- Apache Airflow orchestration
- Prometheus metrics collection
- Grafana visualization dashboards
Innovation & Research Access
Cutting-Edge Research
Direct access to latest research papers, pre-publication findings from our instructor network, and experimental framework implementations.
- • Weekly research paper discussions
- • Beta access to new ML frameworks
- • Collaboration with academic institutions
- • Industry research partnership projects
Industry Connections
Real-world datasets, production system access, and direct mentorship from engineers at leading European technology companies.
- • Production dataset access agreements
- • Guest lectures from industry leaders
- • Internship and job placement pipeline
- • Annual industry advisory board reviews
Integrated Solutions & Packages
Customized combinations and progressive pathways for comprehensive ML engineering mastery
Progressive Learning Paths
Foundation → Production Track
Complete both programs with seamless progression and 20% discount on the second program. Perfect for comprehensive skill development.
Production → Career Package
Advanced technical training followed by intensive career preparation and placement support. Ideal for experienced developers.
Complete Mastery Journey
All three programs in sequence with comprehensive mentorship, guaranteed placement, and lifetime alumni support. Ultimate ML engineering education.
Specialized Combinations
Corporate Training Packages
Customized programs for enterprise teams with on-site delivery, company-specific datasets, and flexible scheduling options.
University Partnership Program
Credit-bearing courses integrated with academic curricula, thesis project support, and research collaboration opportunities.
Alumni Continuing Education
Ongoing professional development with quarterly workshops, annual conference access, and advanced specialization modules.
Flexible Payment Options
Upfront Payment
Pay full amount at enrollment
Early bird pricing until July 30, 2025
Installment Plan
Spread payments over program duration
Interest-free monthly payments
Income Share Agreement
Pay after successful placement
24 months after €60k+ placement
Comprehensive FAQ
Detailed answers about all programs, processes, and services
How do I choose the right program for my experience level?
We provide a comprehensive assessment process to match you with the optimal program. Foundations is ideal for beginners or career changers with basic programming knowledge. Production Systems suits developers with 1-2 years experience seeking advanced technical skills. Career Transformation is perfect for anyone serious about transitioning to ML engineering with guaranteed placement support, regardless of background. Our admissions team conducts a 30-minute consultation to evaluate your goals, timeline, and technical foundation to recommend the best fit.
What's included in the job placement guarantee?
Our Career Transformation program includes a comprehensive 95% placement guarantee. This means if you successfully complete all program requirements, maintain good standing, and actively participate in our placement process, you'll receive a qualifying job offer within 6 months of graduation or we provide full tuition refund. Qualifying offers must be ML engineering roles with salaries above €65,000 EUR in the DACH region. The guarantee includes unlimited interview preparation, resume optimization, and direct introductions to our 50+ hiring partners.
Can I work full-time while taking the Foundations or Production Systems programs?
Yes, both Foundations and Production Systems are designed for working professionals. Classes meet Tuesday/Thursday evenings 7-10 PM CET with Saturday project sessions 10 AM-4 PM CET. We recommend dedicating 15-20 hours per week for optimal success. The Career Transformation program requires full-time commitment (40+ hours weekly) due to intensive capstone projects and interview preparation. We provide detailed study schedules and time management guidance to help you balance work and learning effectively.
What kind of projects will I work on during the programs?
All programs feature real-world projects using actual enterprise datasets and production constraints. Foundations includes computer vision projects (medical image analysis), NLP sentiment analysis for e-commerce, and recommendation systems. Production Systems focuses on building scalable ML pipelines, real-time inference systems, and distributed training implementations. Career Transformation includes three industry capstone projects with actual clients, covering areas like fraud detection for fintech, predictive maintenance for manufacturing, and personalization engines for media companies.
How does the Income Share Agreement work?
Available for Career Transformation students, the ISA requires no upfront payment. After securing employment with annual salary above €60,000 EUR, you pay 15% of your gross monthly salary for 24 months. Payment is capped at 1.8x the original tuition amount. If your salary drops below €60,000 or you become unemployed, payments pause automatically. The ISA includes the same placement guarantee and support services as traditional payment options. This option removes financial barriers while aligning our success with your career outcomes.
What ongoing support do you provide after graduation?
All graduates receive lifetime access to our alumni network, curriculum updates, and career services. This includes quarterly skill workshops, annualCheckenui conference, job transition support, salary negotiation assistance, and networking events. We track career progression and provide ongoing mentorship for promotions and role transitions. Alumni also get priority access to new course modules, beta programs, and speaking opportunities. Our alumni Slack community has 250+ active members sharing opportunities, insights, and collaboration on personal projects.
How do you ensure curriculum stays current with rapidly evolving ML field?
We maintain curriculum relevance through quarterly industry advisory board reviews, continuous feedback from our 50+ hiring partners, and direct involvement of instructors in active ML research and production systems. Our content development team monitors emerging technologies, analyzes job market trends, and integrates new frameworks within 3-6 months of industry adoption. We also beta test new course modules with alumni volunteers and maintain partnerships with major cloud providers for early access to new ML services and tools.
Ready to Begin Your ML Engineering Journey?
Choose your program and start building the career you've always wanted. Next cohort begins August 12, 2025.