Google offers 10 free artificial intelligence courses for beginners. The modules span generative systems, language models, and responsible AI frameworks, and are structured in short bursts designed to be completed quickly.Each course is hosted on the Google Learning Platform and requires no registration fees or advanced technical background. Learners have access to structured content that includes theory, hands-on demonstrations, and tool-based exercises.Overview of the Google Free AI Course CatalogGoogle’s free AI learning catalog includes 10 modular courses that cover everything from introductory concepts to applied machine learning techniques. The program is structured for independent study, with each module designed to be completed in less than an hour or through guided practice sessions.Basic generative AI and language model coursesIntroduction to Generative AI provides short 45-minute modules that explain how generative systems work and how to use Google tools to build applications. Overview of Large-Scale Language Models describes the role of LLM, examples of its use, and ways to improve it. Overview of Responsible AI explains the principles used in ethical AI development and outlines fairness and safety considerations. Prompt Design in Vertex AI focuses on creating text and image generation instructions using Google’s AI platform with hands-on exercises.Model architecture and transformer-based learning toolsImage Generation Overview explains how the system creates realistic visuals from data and provides an overview of the core technology behind image synthesis. Encoder-decoder architecture describes how a machine processes and translates language when summarizing text. The attention mechanism introduces how the model prioritizes relevant information in a sequence. Transformer and BERT models demonstrate progress in understanding contextual language and provide digital badges upon completion.Applied AI projects and generative studio toolsCreating image captioning models allows learners to build systems that combine visual recognition and language generation techniques to describe images. This course focuses on training models that connect image inputs and descriptive text outputs through structured datasets.This course also covers how to evaluate image captioning models using accuracy and relevance metrics across a variety of datasets.Introduction to Generative AI Studio introduces Google’s application building environment for Generative Systems, allowing users to test and deploy their AI-driven ideas through guided demonstrations and interactive tools.Generative AI Studio also provides pre-built templates for application prototyping and supports integration with text and image models. This allows learners to experiment with deployment workflows, instant testing, and iterative improvement of outputs within a controlled environment designed for structured learning across multiple generative AI use cases.Google’s free AI learning lineup includes generative tools, LLM, and transformer models for hands-on skill building1. Encoder/decoder architecture: Understand how machines translate language and summarize text using the building blocks of structured models.2. Introducing responsible AI: Learn how Google applies fairness principles and ethical frameworks to AI development.3. Attention mechanisms: Investigate how AI systems can focus on relevant parts of text and images to improve predictions.4. Introduction to Generative AI: A short introductory course that explains how generative systems create content and applications using Google tools.5. Build an image captioning model: Build a system that combines visual and linguistic techniques to generate descriptive text from images.6. Overview of large-scale language models: Learn how large-scale language models work, where they are used, and how they can be improved.7. Prompt Design with Vertex AI: Practice how to construct prompts that generate accurate text and images using Google’s AI tools.8. Introducing Generative AI Studio: Explore Google’s platform for building, testing, and deploying generative AI applications.9. Transformer and BERT models: Understand the transformer architecture and how BERT improves understanding of context languages.10. Image Generation Overview: Learn how AI systems use data-driven and physics-inspired methods to generate realistic images.
