Introduction to AI and Machine Learning on Google Cloud

This 1-day introductory course provides a clear and practical overview of how artificial intelligence (AI) and machine learning (ML) can be applied on Google Cloud. Participants learn the fundamental concepts of ML, the lifecycle of an AI project, types of models and approaches, and how Google Cloud supports the development and deployment of intelligent applications. The course covers both pre-built AI services (Vision AI, Natural Language AI, Translation AI) and tools for developing custom models, such as Vertex AI, illustrated with practical demonstrations and real-world scenarios.

Duration: 1 day
Level: Beginner
Provider: Google Cloud
Topic: Cloud & infrastructure / Google Cloud

Course outline

What is AI and what is ML
Types of ML problems: supervised, unsupervised, reinforcement
Stages of a machine learning project
The impact of AI in industry
AI services portfolio in Google Cloud
Product categories: pre-built APIs, AutoML, custom models
When to use already trained models vs. when to train your own
Vision AI – image recognition and object detection
Natural Language AI – text analysis, sentiment, entities
Translation AI – automatic translation and multilingual intelligence
Speech-to-Text and Text-to-Speech
Practical demonstrations with Google APIs
What Vertex AI is and its role in the ecosystem
Dataset management, model training and evaluation
Deployment and MLOps
Integrated notebooks, pipelines and model monitoring
Building a simple ML pipeline
Corporate use cases: visualization, text conversion, process automation, classification
Google Cloud case studies
Responsible AI principles at Google Cloud
Risks, bias, transparency and impact

Skills you will gain

Explain the essential concepts of AI and machine learning
Understand the types of ML problems and how to choose a suitable model
Describe the components of an ML pipeline on Google Cloud
Use pre-built AI services for images, language and text
Understand the role of the Vertex AI platform in developing, training and deploying models
Recognize real-world scenarios for applying AI in organizations

Who should attend

Technical and non-technical professionals who want an introduction to AI and ML
Data engineers and machine learning engineers who are just starting out in the Google Cloud ecosystem
Developers and cloud engineers who prepare ML projects
Analysts and data specialists who want to use ready-made models
Professionals embarking on the Professional Machine Learning Engineer certification path

Prerequisites

No advanced programming or machine learning knowledge is required
Familiarity with general cloud concepts can help, but is not mandatory

Upcoming dates

These sessions run online with LLPA partners. Times are shown in Polish time, and the language of delivery is listed for each date.

Date	Times (Polish time)	Language	Status	Price	Action
4 December 2026	08:00–16:00	English	Scheduled	2720 PLN	Request a quote

2720 PLN

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Twenty years
on the same path.

From skills assessment,
through AI-supported learning,
to proven skills.

From need
to delivery.

Over 600,000
people trained.