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Helsinki - Pohjoisesplanadi

NobleProg Helsinki, Pohjoisesplanadi 29, Helsinki, finland, 00100

Ways to get there

  • By train: Get off at Helsinki Central Railway Station. The destination is about 600 m away, roughly a 7–10 minute walk.
  • By metro: Get off near the city centre; the nearest metro station is about 500 m away.
  • By tram: There are tram stops approximately 200 m from the address.
  • Walking: If you're already in central Helsinki, walking is an easy option because the address is directly on Pohjoisesplanadi beside Esplanadi Park.
  • By car/taxi: There is a designated drop-off area in front of Pohjoisesplanadi 29 for arriving vehicles.

For exact public-transport directions from your starting point, HSL's Journey Planner can calculate the route and current schedules.

Subcategories (1)

Kubeflow

Kubeflow

Explore Our Courses

DeepSeek: Advanced Model Optimization and Deployment

 14 Hours

This instructor-led, live training in Helsinki (online or onsite) is aimed at advanced-level AI engineers and data scientists with intermediate-to-advanced experience who wish to enhance DeepSeek model performance, minimize latency, and deploy AI solutions efficiently using modern MLOps practices.

By the end of this training, participants will be able to:

  • Optimize DeepSeek models for efficiency, accuracy, and scalability.
  • Implement best practices for MLOps and model versioning.
  • Deploy DeepSeek models on cloud and on-premise infrastructure.
  • Monitor, maintain, and scale AI solutions effectively.
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MLOps on Kubernetes: CI/CD Pipelines for Machine Learning

 14 Hours
This live training in Helsinki helps intermediate practitioners build automated MLOps pipelines on Kubernetes. Participants design CI/CD workflows, implement GitOps strategies, and deploy ML models using containerized infrastructure for scalable, reproducible machine learning operations.
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Kubeflow Essentials: Build, Train & Serve with Kubernetes

 14 Hours
This hands-on training in Helsinki equips you with the skills to build, train, and serve machine learning models on Kubernetes using Kubeflow. You will learn to navigate the ecosystem, author scalable pipelines, and manage production-ready workloads with best practices.
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Docker for MLOps: End-to-End Pipeline Containerization

 21 Hours
This instructor-led training in Helsinki guides professionals through containerizing complete ML pipelines using Docker. Participants will master building reproducible environments, orchestrating training and inference workloads, and implementing CI/CD for scalable MLOps deployments.
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Kubeflow Fundamentals

 28 Hours

This instructor-led, live training in Helsinki (online or onsite) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.

By the end of this training, participants will be able to:

  • Install and configure Kubeflow on premise and in the cloud.
  • Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
  • Run entire machine learning pipelines on diverse architectures and cloud environments.
  • Using Kubeflow to spawn and manage Jupyter notebooks.
  • Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
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MLOps: CI/CD for Machine Learning

 35 Hours

This instructor-led, live training in Helsinki (online or onsite) is aimed at engineers who wish to evaluate the approaches and tools available today to make an intelligent decision on the path forward in adopting MLOps within their organization.

By the end of this training, participants will be able to:

  • Install and configure various MLOps frameworks and tools.
  • Assemble the right kind of team with the right skills for constructing and supporting an MLOps system.
  • Prepare, validate and version data for use by ML models.
  • Understand the components of an ML Pipeline and the tools needed to build one.
  • Experiment with different machine learning frameworks and servers for deploying to production.
  • Operationalize the entire Machine Learning process so that it's reproduceable and maintainable.
Read more...

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Upcoming Courses

DeepSeek: Advanced Model Optimization and Deployment

2026-12-21 09:30
14 hours
Helsinki - Pohjoisesplanadi
3000 EUR (Online)
3400 EUR (Classroom)

MLOps: CI/CD for Machine Learning

2027-01-04 09:30
35 hours
Helsinki - Pohjoisesplanadi
7500 EUR (Online)
8500 EUR (Classroom)

Docker for MLOps: End-to-End Pipeline Containerization

2027-01-18 09:30
21 hours
Helsinki - Pohjoisesplanadi
4500 EUR (Online)
5100 EUR (Classroom)

MLOps: CI/CD for Machine Learning

2027-02-01 09:30
35 hours
Helsinki - Pohjoisesplanadi
7500 EUR (Online)
8500 EUR (Classroom)

MLOps: CI/CD for Machine Learning

2027-02-15 09:30
35 hours
Helsinki - Pohjoisesplanadi
7500 EUR (Online)
8500 EUR (Classroom)

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