Introduction to AI and machine learning on Google Cloud Training in Denmark

  • Learn via: Online Instructor-Led / Classroom Based / Onsite
  • Duration: 1 Day
  • Level: Intermediate
  • Price: Please contact for booking options
  • Upcoming Date:

Introduction to AI and Machine Learning on Google Cloud is a foundational training program designed for professionals who want to build artificial intelligence and machine learning solutions using Google Cloud technologies. The course introduces the complete Data-to-AI Lifecycle, helping learners understand how Google Cloud supports AI foundations, model development, deployment, and generative AI solutions.

Throughout the training, participants explore powerful Google Cloud services including Vertex AIBigQuery MLAutoMLGenerative AI StudioModel Garden, and various pre-trained AI APIs. The course demonstrates how to build, train, deploy, and manage machine learning models while leveraging Google’s advanced AI infrastructure.

This program is ideal for professionals seeking practical knowledge of Google Cloud's AI ecosystem and provides a strong foundation for developing scalable, production-ready machine learning and generative AI solutions.


We can organize this training at your preferred date and location. Contact Us!

Prerequisites

To gain maximum benefit from this course, participants should have:

  • Basic understanding of Machine Learning concepts
  • Familiarity with SQL
  • Basic Python programming knowledge
  • General awareness of cloud computing concepts (recommended)

Who Should Attend

This course is ideal for:

  • AI Developers
  • Machine Learning Engineers
  • Data Scientists
  • Data Engineers
  • Cloud professionals
  • Software developers building AI applications
  • Professionals interested in Google Cloud AI solutions

What You Will Learn

By the end of this course, learners will be able to:

  • Identify Google Cloud's key AI and ML services.
  • Understand the complete Data-to-AI lifecycle.
  • Select the most appropriate AI development approach.
  • Build machine learning models using Vertex AI.
  • Create models directly in data warehouses using BigQuery ML.
  • Develop ML solutions with AutoML.
  • Integrate pre-trained AI APIs into applications.
  • Build generative AI solutions using Google Cloud tools.
  • Understand MLOps practices and workflow automation.

Training Outline

AI Foundations

Google Cloud AI Ecosystem

  • Introduction to Google Cloud
  • Google's AI strategy and innovation
  • Cloud-based AI solutions
  • Data-driven AI approaches

AI/ML Framework on Google Cloud

  • Google Cloud AI architecture
  • Data and AI services
  • Machine learning lifecycle
  • Google Cloud AI platforms

Google Cloud Infrastructure

  • Cloud infrastructure fundamentals
  • Scalable AI environments
  • Security and performance considerations

Data and AI Products

  • Google Cloud data services
  • AI and analytics tools
  • Integrated data management solutions

ML Model Categories

  • Supervised learning
  • Unsupervised learning
  • Deep learning
  • Predictive modeling approaches

BigQuery ML

  • BigQuery ML
  • SQL-based machine learning
  • Building models directly in BigQuery
  • Analytics and prediction use cases

AI Development Options

AI Development Approaches

  • Types of AI projects
  • Development strategies
  • Solution selection considerations

Pre-trained APIs

  • Pre-trained AI services
  • Vision APIs
  • Natural Language Processing APIs
  • Speech and translation services

Vertex AI

  • Vertex AI
  • End-to-end AI platform
  • Model training and deployment
  • Enterprise AI development workflows

AutoML

  • AutoML
  • No-code machine learning
  • Automated model building
  • Training optimization

Custom Training

  • Custom model development
  • Advanced training techniques
  • Specialized ML use cases

AI Development Workflow

How Machine Learning Works

  • Machine learning fundamentals
  • Learning mechanisms
  • Data and algorithm relationships

ML Workflow

  • Problem definition
  • Data preparation
  • Model development
  • Evaluation processes
  • Production deployment

Data Preparation

  • Data collection
  • Data cleaning
  • Data transformation
  • Feature engineering

Model Development

  • Model selection
  • Training methodologies
  • Performance optimization

Model Serving

  • Model deployment
  • API integration
  • Real-time inference

MLOps and Workflow Automation

  • MLOps
  • Continuous integration
  • Continuous deployment
  • Model lifecycle management

Generative AI

Generative AI Fundamentals

  • Generative AI
  • Large Language Models (LLMs)
  • Foundation Models
  • Prompt Engineering

Duet AI Use Cases

  • Duet AI
  • AI-assisted productivity solutions
  • Intelligent workflow automation

Model Garden

  • Model Garden
  • Pre-built AI models
  • Foundation model access
  • Model selection strategies

Generative AI Studio

  • Generative AI Studio
  • Prompt development
  • Model testing environments
  • Generative AI application development

AI Solutions

  • Enterprise AI solutions
  • Conversational AI
  • Content generation
  • Intelligent automation systems

Hands-On Labs

BigQuery ML Lab

  • Building ML models with SQL
  • Data analytics exercises

Natural Language API Lab

  • NLP service implementation
  • Text analytics applications

AutoML Lab

  • No-code model development
  • Training and evaluation workflows

Generative AI Studio Lab

  • Prompt engineering exercises
  • Generative AI solution development

Why Choose Us

Experience Introduction to AI and machine learning on Google Cloud in Denmark through Bilginç IT Academy's live and interactive virtual classroom environment, accessible from your home, office, or any location. Connect with expert trainers in real time and bring the energy of classroom learning into the digital experience.

  • Live Instructor-Led Sessions: Join scheduled training sessions with your instructor and fellow delegates in real time.
  • Interactive Learning Experience: Take part in discussions, practical exercises, group activities, and Q&A sessions throughout the course.
  • Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
  • Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's long-standing experience in delivering professional training since 1995.
  • Flexible and Scalable Delivery: Access live virtual classrooms from Denmark and worldwide, with flexible planning options for individual and corporate training needs.

Experience Introduction to AI and machine learning on Google Cloud in a focused classroom environment in Denmark. Bilginç IT Academy's carefully selected training venues provide a professional setting where delegates can interact directly with expert trainers and peers.

  • Experienced Trainers: Learn from specialists with extensive field experience and real-world knowledge.
  • Professional Training Venues: Attend courses in comfortable, well-equipped classrooms designed to support effective learning.
  • Focused Classroom Experience: Benefit from limited class sizes that encourage discussion, interaction, and personalized support.
  • Quality-Driven Learning: Develop practical skills through structured, up-to-date, and professionally designed training content.

Meet your team's training needs with Bilginç IT Academy's onsite Introduction to AI and machine learning on Google Cloud in Denmark solution, delivered at your office or preferred location. Align your team's development with your business goals through a training experience tailored to your organization.

  • Tailored Course Content: Adapt the training program to your organization's projects, team structure, and specific business requirements.
  • Time and Cost Efficiency: Reduce travel, accommodation, and operational costs while maximizing the value of your training investment.
  • Team-Focused Learning: Help your employees develop around the same knowledge base and strengthen collaboration across your organization.
  • Simplified Planning and Tracking: Manage the training process, participant development, and organizational requirements with greater control.


Contact us for more detail about our trainings and for all other enquiries!

Frequently asked questions about Introduction to AI and machine learning on Google Cloud Training Course in Denmark (FAQ)

This training is suitable for individuals who want to start learning AI and machine learning, including business analysts, data analysts, developers, and non-technical professionals. It provides a strong introduction to AI solutions on Google Cloud.

No advanced technical knowledge is required. The training explains AI and machine learning concepts from a foundational level. Basic computer skills and familiarity with data concepts are sufficient.

The training covers services such as Vertex AI, AutoML, and Google Cloud AI APIs. Participants learn how these tools are used and how they can be applied to solve business problems.

The training explains AI and machine learning concepts from the basics with practical examples. Participants learn about approaches such as supervised and unsupervised learning and how they are applied in real-world scenarios.

Participants gain an understanding of how AI and ML solutions can be integrated into business processes. They can contribute more effectively to data-driven decision-making, automation, and predictive analytics initiatives.

Yes, the training includes hands-on scenarios such as working with Google Cloud AI tools, building simple models, and analyzing datasets. Participants gain practical experience through real-world examples.

This training provides a strong introduction to AI and machine learning. However, building an advanced AI career requires additional skills such as Python, data science, model development, and mathematical foundations.

This training is valuable for roles such as Data Analyst, Business Analyst, entry-level AI/ML roles, product managers, and professionals working on AI-driven projects in Google Cloud environments.

Absolutely. We do not only host trainings at public centers; we can also conduct them directly at your premises across Denmark. We can customize the curriculum to meet your team's specific needs and organize the session at your preferred location and date within Denmark.

Yes, we prioritize location flexibility. We offer live-streaming (hybrid) support for most of our trainings, synchronized with the Denmark time zone. If you are unable to visit our location, you can join our physical classroom setting interactively via our digital platforms and participate in hands-on workshops remotely from anywhere in Denmark.

Introduction to AI and machine learning on Google Cloud Training Course in Denmark Schedule

Join our public courses in our Denmark facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

We can organize this training at your preferred date and location.
09 juli 2026 (1 Day)
Copenhagen, Aarhus, Odense
12 juli 2026 (1 Day)
Copenhagen, Aarhus, Odense
14 juli 2026 (1 Day)
Copenhagen, Aarhus, Odense
15 juli 2026 (1 Day)
Copenhagen, Aarhus, Odense
16 juli 2026 (1 Day)
Copenhagen, Aarhus, Odense
17 juli 2026 (1 Day)
Copenhagen, Aarhus, Odense
10 august 2026 (1 Day)
Copenhagen, Aarhus, Odense
23 august 2026 (1 Day)
Copenhagen, Aarhus, Odense

Denmark consistently ranks as one of the most digitally advanced nations in the world, with Copenhagen and Aarhus serving as vibrant centers for green-tech and digital government solutions. The country’s commitment to digital transformation is backed by top-tier institutions like the Technical University of Denmark (DTU), which fosters innovation in sustainable energy software and biotechnology. Denmark’s business environment is highly digitized, requiring a workforce that is proficient in the latest enterprise solutions and cloud frameworks. Our training solutions in Denmark are focused on high-demand skills such as DevOps, Cyber Defense, and Agile management. We provide the expertise necessary for professionals to excel in a highly efficient, tech-driven economy that prioritizes innovation, sustainability, and digital integration.

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