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Deploy models to SageMaker like a professional ML engineer

Bring your skills to the next level

  • • Overwhelmed by cloud deployment and MLOps complexity? We break it down step by step.
  • • Move your models from local experiments to scalable, production-grade pipelines on AWS SageMaker.
  • • Learn how to automate, deploy, and monitor ML workflows with confidence.
  • • Take home production-ready code and integrate it into your own projects.
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ML Training Illustration

This Training is for builders

Hands-on, to the point and you will write plenty of code

Who You Are

Data Scientist

Who are overwhelmed by the complexity of taking models from your local machine to scalable, production-ready cloud deployments—and want to learn how to do it the right way, following MLOps best practices.

Technical Professional or Software Engineer

Who want to build AI powered products according to industry best practices

Technical Team Lead

Who want to provide their team with the skills to build end-to-end ML workflows

What You'll Build

End-to-End ML Systems

  • •Production-ready models deployed on AWS SageMaker
  • •Automated ML pipelines for training, validation, and deployment
  • •Monitoring systems that track model performance in real-time
  • •Scalable infrastructure that handles real-world data volumes
  • •CI/CD pipelines automatically delivering your new pipeline definitions to AWS

Ready to Build Production ML Systems?

Join builders who are already shipping AI-powered solutions

Start Building Today

Training Materials

A comprehensive 2-day intensive course covering MLOps fundamentals and AWS ecosystem. We offer a adaptive course for companies, with a focus on your specific use cases as well as a more general course for individuals.

Duration

2 Days Intensive

Format

Theory + Hands-on

Level

Foundational to Advanced

1

MLOps Foundations & AWS Ecosystem

Morning Session

  • •Introductions: Get to know trainers, participants, and training objectives
  • •MLOps Fundamentals: Principles, lifecycle, and differences from traditional operations
  • •AWS Services Overview: AI/ML services and their roles in MLOps

Afternoon Session

  • •Deep Dive into SageMaker: Environment, compute engine, and pipeline basics
  • •Environment Setup: Hands-on practical exercise
  • •SageMaker Studio: Notebook basics through guided exercises
2

Machine Learning Pipelines

Morning Session

  • •Steps to Pipelines: Transitioning from individual steps to full pipelines
  • •Artifact Flows: Understanding data flow between pipeline steps

Afternoon Session

  • •Model Registry: Definition and practical understanding
  • •Inference Types: Real-time vs batch inference and use cases
  • •API Endpoints: Hands-on creation and deployment

Extend Your Learning Journey

For teams ready to dive deeper, we offer additional modules covering advanced MLOps concepts and production best practices.

Advanced Topics

Bring Your Own Container (BYOC), Docker

Production Monitoring

SageMaker Model Monitor, CloudWatch

CI/CD & Governance

Pipeline definitions, cost optimization

Data Governance

Optional module based on group needs

Our Learning Approach

Each concept is reinforced through a balanced blend of theory, hands-on exercises, and peer learning to ensure comprehensive understanding of MLOps, ML pipelines, and AWS cloud services.

Theoretical Foundation
Practical Exercises
Collaborative Learning

Choose Your Learning Path

Whether you're an individual looking to advance your career or an organization seeking to transform your team, we have the perfect training solution tailored to your needs.

Enterprise Training

Comprehensive team training with custom curriculum adaptation, provinding a basis for your team to start building production ML pipelines.

Focus: Company-Specific Use Cases

Training is tailored to your organization's specific challenges, industry context, and business objectives. We work with data and models mimicking your own, leaving you with relevant skills (and code) to solve your actual business problems.

Custom curriculum for your use cases, depending how advanced your team is.
On-site or virtual delivery
Implementation support included
Volume pricing available
Adaptable Approach

Curriculum and examples are customized to match your industry, technology stack, and specific business challenges.

Individual Certification

Advance your career with industry-recognized knowledge and skills on MLOps. We'll help you get started with the right tools and techniques.

Focus: Standardized Excellence

Structured curriculum following industry best practices and standards. Comprehensive coverage of fundamental concepts with practical, proven examples. Whether you are an individual working in a team, or looking for a job we have you covered.

Self-paced or instructor-led
Career advancement support
Groupchat to discuss progress and any questions
Lifetime community access
Proven Framework

Battle-tested curriculum based on industry standards and successful implementations across various domains.

Key Difference

Enterprise: Problem-Driven

We start with your specific business challenges and adapt our training to solve your actual problems using your real data and context.

Individual: Foundation-First

We provide comprehensive foundational knowledge using proven methodologies and industry-standard examples that apply universally.

Companies that trust us to train their people

We've trained hundreds of people in the past years, and we're proud to have some of the best companies in the Netherlands as our clients

Learn from Industry-Leading Experts

Our world-class instructors combine deep academic knowledge with real-world experience from top tech companies. They've trained thousands of professionals and are passionate about sharing their expertise.

Dr. Pascal Golec

Dr. Pascal Golec

Co-Founder at Heights

Data Science, MLOps and Backend Engineering

Founder of Heights with extensive experience in data science and machine learning operations. Specialized in fraud detection and cloud engineering solutions.

Credentials & Background

  • PhD in Econometrics
  • 10+ years in the Data Field
  • Founder and MLOps professional

Core Expertise

Cloud EngineeringNLPFraud DetectionMLOps

"Pascal's deep understanding of AI fundamentals combined with practical industry experience makes him an exceptional instructor."

Wilfred de Graaf

Wilfred de Graaf

Co-Founder at Heights

Data Science and Analytics as well as opportunity identification

Led Data Science teams at Rabobank and Rewire to implement end-to-end use cases. Expert in identifying business opportunities through data analytics.

Credentials & Background

  • Keynote speaker at WEF
  • Former Lead Data Scientist at Rabobank
  • Co-founder at Heights

Core Expertise

PythonSQLApache SparkData Visualization

"Wilfred brings unparalleled expertise in scaling data solutions for millions of users."

Maarten Rottier

Maarten Rottier

Head of MLOps

MLOps, Cloud Engineering and Backend Engineering

Head of MLOps at Heights with expertise in production machine learning systems and cloud infrastructure. Specialized in scaling ML solutions and backend engineering.

Credentials & Background

  • MLOps Expert
  • Cloud Engineering Specialist
  • Backend Engineering Professional

Core Expertise

DockerKubernetesAWS/AzureMLflow

"Maarten's practical approach to MLOps and cloud engineering makes complex concepts accessible and actionable."

Our Commitment to Excellence

Proven Track Record

Over 1,000 professionals trained in 5+ different countries

Industry Recognition

A curriculum designed by leading industry experts

Continuous Learning

Updated curriculum reflecting latest industry trends and technologies