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Apply your skills in Google Cloud console

Mahesh Fulsundar

Date d'abonnement : 2026

Ligue d'Or

6199 points
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation Earned mars 22, 2026 EDT
AI Boost Bites: Become an AI Art Director for Your World Earned mars 17, 2026 EDT
AI Boost Bites: Bring your photos to life with AI Earned mars 17, 2026 EDT
AI Boost Bites: NotebookLM Video Overviews Earned mars 17, 2026 EDT
AI Boost Bites: Animated Charts with Gemini Earned mars 17, 2026 EDT
AI Boost Bites: Gemini Slide Summaries Earned mars 17, 2026 EDT
AI Boost Bites: NotebookLM Reports Earned mars 15, 2026 EDT
AI Boost Bites: Email Content Creation Earned mars 13, 2026 EDT
AI Boost Bites: Create the Perfect Portrait Earned mars 13, 2026 EDT
AI Boost Bites: Intro to NotebookLM Earned mars 13, 2026 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack Earned mars 13, 2026 EDT
AI Boost Bites: Tame Your Inbox with AI Earned mars 13, 2026 EDT
AI Boost Bites: AI Power-Ups for Google Workspace Earned mars 13, 2026 EDT
AI Boost Bites: Your Personal Feedback Agent Earned mars 13, 2026 EDT
AI Boost Bites: Prompting like a Pro with Google Workspace Earned mars 13, 2026 EDT
Gemini for end-to-end SDLC Earned mars 13, 2026 EDT
Prompt Design in Vertex AI Earned mars 12, 2026 EDT
Introduction to Vertex AI Studio Earned mars 11, 2026 EDT
Attention Mechanism Earned mars 11, 2026 EDT
Transformer Models and BERT Model Earned mars 11, 2026 EDT
Create Image Captioning Models Earned mars 11, 2026 EDT
Encoder-Decoder Architecture Earned mars 11, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI Earned mars 11, 2026 EDT
Introduction to Image Generation Earned mars 11, 2026 EDT
Introduction to Responsible AI Earned mars 11, 2026 EDT
Introduction to Large Language Models Earned mars 11, 2026 EDT
Introduction to Generative AI Earned mars 11, 2026 EDT

This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production. Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

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In this video, you'll learn to art direct your images in the Gemini app. You'll see how to use multi-turn editing to furnish an empty room step-by-step, and how to "remix" a photo by applying the color and texture of a butterfly's wings to a pair of rainboots.

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In this video, you'll learn to turn still images into dynamic videos using Gemini. Master the art of prompting for motion and audio to animate sketches and photographs, instantly elevating your visual storytelling.

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This video covers how to use the Video Overviews feature in NotebookLM to automatically generate a short explainer video based on your source documents.

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In this video, you'll learn to create an animated bar chart race using Gemini Canvas. You'll see how to write a prompt to visualize data over time and then use a follow-up prompt to refine the animation, such as slowing it down for a presentation.

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This video covers how to use Gemini in Slides to automatically generate meeting recaps and draft follow-up emails, which can streamline your post-meeting workflow and save you time.

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This video covers how NotebookLM's Reports feature dynamically suggests formats to help you create customized, trustworthy analyses of your documents with ease.

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This video covers how to use Gemini in Gmail to draft new emails, refine their tone, respond with context from Drive files, and use smart reply suggestions.

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In this video, you'll learn to create imaginative portraits in the Gemini app that maintain your likeness. You'll see how to use the "Subject, Action, Scene, Style" formula for better prompts, transport yourself into a vintage photo, and combine a photo of yourself and your dog into one new image.

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This video covers how to use NotebookLM as a personal research assistant by adding sources, asking questions, and generating new content formats based on your documents.

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This video covers how to eliminate tedious manual data entry using Gemini. Learn how to take a picture or screenshot of data (from PDFs, paper, or images) and prompt Gemini to instantly convert it into a structured Google Sheet. Discover this simple hack to save countless hours transcribing data, turning Gemini into your personal data entry assistant. Just snap, prompt, and export!

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This video covers how to use Gemini in Gmail to summarize emails, find information, and draft replies, helping you manage your inbox more efficiently.

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This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.

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This video covers how to build a personalized "Work with Me" agent using Gemini Gems, which helps streamline foundational feedback and makes your meetings more strategic and efficient.

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This video covers prompt engineering fundamentals for effective AI communication. Learn a simple framework (Persona, Task, Context, Format) to craft clear prompts, getting better, faster results from Gemini in Google Workspace. Discover how to use natural language, be specific, and iterate for optimal AI assistance.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC). Duet AI was renamed to Gemini, our next-generation model.

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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.

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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.

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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.

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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.

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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images

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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.

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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.

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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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