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Leena Dighole

Jest członkiem od 2022

Liga diamentowa

70611 pkt.
Coordinate Multiple Agents Earned kwi 3, 2026 EDT
Google DeepMind: 07 Accelerate Your Model Earned mar 28, 2026 EDT
Google DeepMind: Train A Small Language Model Earned mar 10, 2026 EDT
Architect Customer Engagement Suite with Google AI Earned lut 16, 2026 EST
Manage Agent Memory and State Earned lut 16, 2026 EST
Add Agent Capabilities With Tools Earned lut 16, 2026 EST
Build Agents with Agent Development Kit (ADK) Earned lut 16, 2026 EST
Create Your First Gemini Enterprise Application Earned lut 14, 2026 EST
Enterprise Agents and Use Cases Earned lut 14, 2026 EST
Introduction to AI Agents Earned lut 14, 2026 EST
Conversational AI and its Engagement Framework Earned sty 12, 2026 EST
Optimize Agent Behavior Earned sty 11, 2026 EST
Build Your First Agent with Agent Development Kit (ADK) Earned sty 11, 2026 EST
Agent Fundamentals Earned sty 11, 2026 EST
AI Infrastructure: Networking Techniques Earned sty 7, 2026 EST
Implement DevOps Workflows in Google Cloud Earned sty 6, 2026 EST
Deploy Kubernetes Applications on Google Cloud Earned sty 6, 2026 EST
Machine Learning Operations (MLOps): Getting Started Earned sty 6, 2026 EST
Optimize Costs for Google Kubernetes Engine Earned sty 6, 2026 EST
Manage Kubernetes in Google Cloud Earned sty 6, 2026 EST
Implement CI/CD Pipelines on Google Cloud Earned sty 6, 2026 EST
Using the Google Cloud Speech API Earned sty 6, 2026 EST
Conversational Insights Earned gru 28, 2025 EST
AI Infrastructure: Storage Options Earned gru 22, 2025 EST
AI Infrastructure: Deployment Types Earned gru 21, 2025 EST
Introduction to Google Workspace with Gemini Earned gru 13, 2025 EST
How to Use TPUs for Inference Earned lis 28, 2025 EST
Architecting an AI Inference Stack Earned lis 28, 2025 EST
Google DeepMind: 04 Discover The Transformer Architecture Earned lis 22, 2025 EST
Google DeepMind: 03 Design And Train Neural Networks Earned lis 20, 2025 EST
Google DeepMind: 02 Represent Your Language Data Earned lis 20, 2025 EST
AI Boost Bites: Notes to Sheets with Gemini Earned lis 17, 2025 EST
AI Boost Bites: Gemini Calendar Hacks in Gmail Earned lis 17, 2025 EST
AI Boost Bites: Build Slides Fast with Gemini Earned lis 17, 2025 EST
AI Boost Bites: Talk to Your Data in Sheets Earned lis 17, 2025 EST
AI Boost Bites: AI Magic in a Sheets Cell Earned lis 17, 2025 EST
AI Boost Bites: Create ‘What If’ Scenarios with AI Earned lis 17, 2025 EST
AI Boost Bites: Become a Creative Mashup Artist Earned lis 17, 2025 EST
AI Boost Bites: Become an AI Art Director for Your World Earned lis 17, 2025 EST
AI Boost Bites: Create the Perfect Portrait Earned lis 17, 2025 EST
AI Boost Bites: Advanced Analysis in Sheets Earned lis 17, 2025 EST
AI Boost Bites: Research Hacks with NotebookLM Earned lis 17, 2025 EST
AI Boost Bites: Find the Story in Your Data Earned lis 17, 2025 EST
AI Boost Bites: Supercharge Research with Gemini Earned lis 17, 2025 EST
AI Boost Bites: Streamline Event Planning with AI Earned lis 17, 2025 EST
AI Boost Bites: Make Any Big Purchase with Confidence Earned lis 17, 2025 EST
AI Boost Bites: Gamify Your Study Guides Earned lis 17, 2025 EST
AI Boost Bites: Get Your Competitor's Playbook in Minutes Earned lis 17, 2025 EST
AI Boost Bites: Build a Personalized Weather App Earned lis 17, 2025 EST
AI Boost Bites: Animated Charts with Gemini Earned lis 17, 2025 EST
AI Boost Bites: Turn Your Ideas into Animated Art Earned lis 17, 2025 EST
AI Boost Bites: Your Personal AI Tutor Earned lis 17, 2025 EST
AI Boost Bites: Create a 3D Solar System Earned lis 17, 2025 EST
AI Boost Bites: Create Your Own Productivity Tools Earned lis 17, 2025 EST
AI Boost Bites: Guided Learning with Gemini Earned lis 17, 2025 EST
AI Boost Bites: Create Your Own Retro Arcade Game Earned lis 17, 2025 EST
AI Boost Bites: Become a "Vibe DJ" Earned lis 17, 2025 EST
AI Boost Bites: Create Your Ultimate College Scouting Report Earned lis 17, 2025 EST
AI Boost Bites: One-Click Campaign Visuals Earned lis 17, 2025 EST
AI Boost Bites: From Napkin Sketch to Functional App Earned lis 17, 2025 EST
AI Boost Bites: NotebookLM Reports Earned lis 17, 2025 EST
Enterprise Search on Generative AI App Builder Earned lis 6, 2025 EST
Generative AI for Healthcare Earned lis 6, 2025 EST
Google DeepMind: 01 Build Your Own Small Language Model Earned lis 5, 2025 EST
AI Boost Bites: Your Personal Feedback Agent Earned paź 29, 2025 EDT
AI Boost Bites: Presentation Scripts with Gemini Earned paź 29, 2025 EDT
Build Custom Processors with Document AI [Deprecated] Earned paź 6, 2025 EDT
Classify Images with TensorFlow on Google Cloud Earned paź 6, 2025 EDT
Automate Data Capture at Scale with Document AI Earned paź 6, 2025 EDT
Analyze Speech and Language with Google APIs Earned wrz 27, 2025 EDT
Get Started with Sensitive Data Protection Earned wrz 27, 2025 EDT
Analyze Images with the Cloud Vision API Earned wrz 27, 2025 EDT
Store, Process, and Manage Data on Google Cloud - Command Line Earned wrz 27, 2025 EDT
Deploy and Scale AI Models with Cloud Run Earned wrz 27, 2025 EDT
AI Boost Bites: Project Notebooks Earned wrz 27, 2025 EDT
AI Boost Bites: NotebookLM Video Overviews Earned wrz 27, 2025 EDT
AI Boost Bites: Discover Sources in NotebookLM Earned wrz 27, 2025 EDT
AI Boost Bites: NotebookLM Mind Maps Earned wrz 27, 2025 EDT
AI Boost Bites: Intro to NotebookLM Earned wrz 27, 2025 EDT
AI Boost Bites: Email Content Creation Earned wrz 27, 2025 EDT
AI Boost Bites: Create Docs in Seconds Earned wrz 27, 2025 EDT
AI Boost Bites: AI Power-Ups for Google Workspace Earned wrz 27, 2025 EDT
AI Boost Bites: Tame Your Inbox with AI Earned wrz 26, 2025 EDT
AI Boost Bites: Gemini Slide Summaries Earned wrz 19, 2025 EDT
AI Boost Bites: Automate tasks with Gemini and Apps Script Earned wrz 16, 2025 EDT
AI Boost Bites: Poke Holes in Your Strategy Earned wrz 16, 2025 EDT
AI Boost Bites: Personalization with customized prompts Earned wrz 16, 2025 EDT
AI Boost Bites: Prompting like a Pro with Google Workspace Earned wrz 16, 2025 EDT
AI Boost Bites: Content Generation with Gemini Made Easy Earned wrz 16, 2025 EDT
AI Boost Bites: NotebookLM for Market Research Earned wrz 15, 2025 EDT
Configure Gemini Code Assist for Organizations Earned wrz 5, 2025 EDT
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud Earned sie 30, 2025 EDT
Use Machine Learning APIs on Google Cloud Earned sie 30, 2025 EDT
Model Armor: Securing AI Deployments Earned sie 23, 2025 EDT
AI Infrastructure: Cloud TPUs Earned sie 13, 2025 EDT
AI Infrastructure: Cloud GPUs Earned sie 13, 2025 EDT
AI Infrastructure: Introduction to AI Hypercomputer Earned sie 13, 2025 EDT
Analyze and Reason on Multimodal Data with Gemini Earned sie 5, 2025 EDT
Analyze Sentiment with Natural Language API Earned sie 5, 2025 EDT
Gemini for Data Scientists and Analysts Earned sie 5, 2025 EDT
Generative AI Explorer - Vertex AI Earned lip 15, 2025 EDT
Explore Generative AI with the Gemini API in Vertex AI Earned lip 6, 2025 EDT
Build Infrastructure with Terraform on Google Cloud Earned lip 6, 2025 EDT
Gen AI Agents: Transform Your Organization Earned cze 19, 2025 EDT
Gen AI Apps: Transform Your Work Earned cze 19, 2025 EDT
Gen AI: Navigate the Landscape Earned cze 19, 2025 EDT
Introduction to Security in the World of AI Earned cze 19, 2025 EDT
Odpowiedzialna AI dla deweloperów: prywatność i bezpieczeństwo Earned cze 19, 2025 EDT
Odpowiedzialna AI dla deweloperów: interpretowalność i przejrzystość Earned cze 19, 2025 EDT
Odpowiedzialna AI dla deweloperów: obiektywność i uprzedzenia Earned cze 19, 2025 EDT
AI Boost Bites: No-Code Sheets & Scripts Earned cze 19, 2025 EDT
AI Boost Bites: Amplify Exec Voices with AI Earned cze 19, 2025 EDT
AI Boost Bites: Exec Summaries with Gemini Gems Earned cze 19, 2025 EDT
AI Boost Bites: "Eat the Frog" with NotebookLM Earned cze 19, 2025 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack Earned cze 19, 2025 EDT
AI Boost Bites: NotebookLM for Competitive Edge Earned cze 19, 2025 EDT
AI Boost Bites: TL;DR with Gemini in Docs & Drive Earned cze 19, 2025 EDT
AI Boost Bites: Customer insights with NotebookLM Earned cze 19, 2025 EDT
AI Boost Bites: Gemini Gems – Your ultimate marketing sidekick Earned cze 19, 2025 EDT
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI Earned maj 14, 2025 EDT
Gen AI: Unlock Foundational Concepts Earned maj 14, 2025 EDT
Gen AI: Beyond the Chatbot Earned maj 7, 2025 EDT
Enhance Gemini Model Capabilities Earned maj 6, 2025 EDT
Build Real World AI Applications with Gemini and Imagen Earned mar 9, 2025 EDT
Create Generative AI Apps on Google Cloud Earned mar 9, 2025 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG Earned mar 4, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation Earned lut 14, 2025 EST
Vector Search and Embeddings Earned lut 14, 2025 EST
Introduction to Security in the World of AI Earned lut 13, 2025 EST
Machine Learning Operations (MLOps) for Generative AI Earned lut 7, 2025 EST
Prompt Design in Vertex AI Earned lut 7, 2025 EST
Build a Certification Study Guide: PMLE Earned paź 21, 2024 EDT
Create Image Captioning Models Earned lut 14, 2024 EST
Introduction to Vertex AI Studio Earned lut 14, 2024 EST
Transformer Models and BERT Model Earned lut 14, 2024 EST
Encoder-Decoder Architecture Earned lut 13, 2024 EST
Attention Mechanism Earned lut 13, 2024 EST
Introduction to Image Generation Earned lut 13, 2024 EST
Generative AI Fundamentals - Polski Earned lut 10, 2024 EST
Responsible AI: Applying AI Principles with Google Cloud - Polski Earned lut 10, 2024 EST
Introduction to Responsible AI - Polski Earned lut 7, 2024 EST
Introduction to Large Language Models - Polski Earned lut 7, 2024 EST
Introduction to Generative AI - Polski Earned sie 8, 2023 EDT

Learn to coordinate multiple specialized agents working together. This lesson teaches you when to use multi-agent systems, how to orchestrate agents with workflow patterns, and how agents communicate through shared state. By the end, you’ll build a complete multi-agent application.

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Train more powerful models with a single GPU. In this course, you will learn how hardware can speed up model training and the key considerations when training models on a GPU. First, you will learn how to estimate the number of computations and the amount of computer memory required to train large neural networks. You will then discover techniques for reducing the computing and memory requirements when training a model. Techniques which you will apply for fine-tuning a Gemma model with 4 billion parameters. Finally, you will consider the potential environmental impacts of machine learning, with a focus on where questions of energy, water, and e-waste intersect with justice and equity.

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Complete the advanced Google DeepMind: Train A Small Language Model skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Access this lab at no-cost by signing up for the no-cost subscription. Receive 35 free credits each month!

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In this course, you'll dive deep into the essential topics you need to know to design, build, and maintain a powerful CES solution. Get ready to transform your understanding of what's possible and create an architecture that drives customer satisfaction. This course is designed to introduce you to the architecture of the Customer Engagement Suite (CES). You'll explore the main considerations for building and implementing Conversational AI solutions including key architectural components and integrations. You'll also explore how Conversational AI interacts with Vertex AI and get a high-level overview of the key features of the Conversational AI Platform.

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You've built basic LLM agents that respond to queries—now let's make them stateful. Use session state to build agents that maintain context, remember user preferences, and provide personalized experiences. Transform agents from stateless responders to intelligent assistants.

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You’ve built agents with advanced configuration—now give them real-world capabilities. Equip agents with tools that enable searching the web, executing code, querying databases, and performing custom actions. Transform agents from intelligent responders into capable assistants that take action.

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Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems.

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Create your first Gemini Enterprise application to earn a skill badge! Connect diverse data sources to your application to build a powerful, unified search and analysis engine. Master advanced capabilities like deep research agents, multi-agent ideation, and NotebookLM for focused analysis.

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Discover how AI agents drive business impact. You’ll map agent types to your KPIs and explore use cases that solve real bottlenecks. Then, learn how Gemini Enterprise empowers you to build and orchestrate the right agents—from no-code to high-code solutions.

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Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.

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Transform your understanding of customer service with this course on the Customer Engagement Suite (CES) and its powerful generative AI capabilities. You'll start by tracing the journey of contact centers, understanding how they've evolved and where gen AI is propelling them next. Then, you'll gain a deep understanding of the core building blocks within the CES solution, seeing how each component contributes to delivering exceptional customer experiences. The course concludes by exploring the robust business case for CES, along with practical use cases and the various user personas that benefit from this innovative solution.

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You’ve built your first agent—now it’s time to take it further. In this course, you’ll advance your skills by learning how to turn a basic AI agent into a sophisticated, precise assistant—applying advanced instructions, model selection, planning capabilities, and structured output patterns. Join the community forum for questions and discussions

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Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK). In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior, taking what you learned in course 1 and applying it to working code.

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AI Agents represent a major shift beyond traditional large language models (LLMs): instead of simply generating text-based solutions, they can also act autonomously to execute them. This course introduces the fundamentals of AI Agents, how they differ from LLM APIs, and where they add value in the real world. Based on Google’s agents whitepaper, it provides the theoretical foundation needed before writing your first lines of agent code—ideal for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior (and not just text generation). Join the community forum for questions and discussions.

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Welcome to the "AI Infrastructure: Networking Techniques" course. In this course, you'll learn to leverage Google Cloud's high-bandwidth, low-latency infrastructure to optimize data transfer and communication between all the components of your AI system. By the end, you'll grasp the critical role networking plays across the entire AI pipeline from data ingestion and training to inference and be able to apply best practices to ensure your workloads run at maximum speed.

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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating git repositories with Cloud Source Repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.

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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.

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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.

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Complete the intermediate Optimize Costs for Google Kubernetes Engine skill badge course to demonstrate skills in the following: creating and managing multi-tenant clusters, monitoring resource usage by namespace, configuring cluster and pod autoscaling for efficiency, setting up load balancing for optimal resource distribution, and implementing liveness and readiness probes to ensure application health and cost-effectiveness.

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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.

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Earn the intermediate skill badge by completing the Implement CI/CD Pipelines on Google Cloud skill badge course where you learn how to use Artifact Registry, Cloud Build, and Cloud Deploy. You interact with the Google Cloud console, Google Cloud CLI, Cloud Run, and GKE. This course teaches you how to build continuous integration pipelines, store and secure artifacts, scan for vulnerabilities, attest to the validity of approved releases. Additionally, you get hands-on experience deploying applications to both GKE and Cloud Run.

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Earn a skill badge by completing the Using the Google Cloud Speech API skill badge course, where you learn how create a Speech-to-Text API request, transcribe audio speech to text, and transcribe speech.

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In this course you will learn how to leverage Conversational Insights to uncover hidden information from your contact center data to increase operational efficiency and drive data-driven business decisions.

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In this course, you’ll take a comprehensive journey through the storage solutions available on Google Cloud, specifically tailored for AI and high-performance computing (HPC) workloads. You’ll learn how to choose the right storage for each stage of the ML lifecycle. You’ll explore how to optimize for I/O performance during training, manage massive datasets for data preparation, and serve model artifacts with low latency. Through practical examples and demonstrations, you’ll gain the expertise to design robust storage solutions that accelerate your AI innovation.

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This course provides a comprehensive guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud. Through a series of lessons and practical demonstrations, you’ll explore diverse deployment strategies, ranging from highly customizable environments using Google Compute Engine (GCE) to managed solutions like Google Kubernetes Engine (GKE). Specifically, you’ll learn how to create clusters and deploy GKE for inference.

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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this learning path, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Workspace.

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This course is for developers interested in learning how to use TPUs for inference—from architecture to deployment, and how to solve common implementation challenges.

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This course is designed for developers looking to build an optimized AI inference stack on Google Cloud. Whether you’re working with GPUs or TPUs, you’ll explore the fundamental components of an inference stack, learn design principles for maximizing performance and reliability, and explore practical techniques to take your workloads from 0 to 1.

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In this Google DeepMind course you will discover the mechanisms of the transformer architecture. You will investigate how transformer language models process prompts to make context-sensitive next-token predictions. Through practical activities you will explore the attention mechanism, visualize attention weights, and encounter advanced concepts like masked attention and multi-head attention. You will also learn other techniques that are necessary to build neural networks that are well-suited to be used as language models. Finally, through activities on values, stakeholder mapping and community engagement, you will practice concrete tools for ensuring AI projects are developed with communities, not just for them.

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In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.

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In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.

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In this video, you'll learn to use Gemini in Google Sheets to automatically generate organized trackers from unstructured data. You'll learn how to write a prompt that references other Google Drive files using the "@" symbol. You'll also see how Gemini builds a fully formatted, color-coded table with drop-down menus based on the data in your notes, saving you significant manual effort.

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In this video, you'll learn to use Gemini in Google Workspace to manage your calendar from your Gmail inbox. You'll learn how to ask Gemini about your schedule in the side panel and how to create new events without switching apps. You'll also learn how to use Gemini's one-click scheduling feature when it automatically detects event details in an email.

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In this video, you'll learn to use Gemini in Google Slides to build polished presentations efficiently. You'll see how to create slides by referencing content directly from your Google Drive files using the "@" symbol. You'll also learn to generate custom, professional images from a simple text prompt to visually enhance your presentation.

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In this video, you'll learn to use the "Ask Gemini" feature in Google Sheets to manage your data with natural language. You'll see how to ask Gemini to create dropdowns, highlight sales data, create a pivot table, filter by month, and sort by revenue.

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In this video, you'll learn to use the =AI() function in Google Sheets to automate your work. You'll see how to generate text like slogans, summarize paragraphs of customer feedback, and categorize data by classifying inquiries and analyzing sentiment.

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In this video, you'll learn to create "what if" scenarios using AI's reasoning. You'll see how to set a "before" scene with a person holding a cake, prompt an action by asking "what would happen if they tripped?", and let the AI generate the plausible "after" image of the cake falling.

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In this video, you'll learn the "creative mashup artist" technique for combining images. You'll see how to generate a subject and a scene as two separate images, and then use a final blending prompt to fuse the astronaut from the first image and the court from the second into one new picture.

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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 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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In this video, you'll learn to use Gemini in Google Sheets for advanced data analysis. You'll learn how to create data visualizations, like a scatter plot, using a simple prompt. You'll also learn how to ask Gemini to analyze your data for strategic insights and recommendations, such as how to save money.

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In this video, you'll learn to use NotebookLM to manage a large-scale research project. You'll see how to upload all your documents to get summaries, ask deeper strategic questions to find key insights, and use the audio feature to listen to your findings on the go.

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In this video, you'll learn to use NotebookLM to analyze raw data and find compelling stories. You'll see how to ground the AI in your specific documents, prompt it to generate newsworthy PR claims, and ask it to find hidden correlations between different data points to uncover new insights.

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In this video, you'll learn pro tips for conducting thorough competitive research with Gemini Deep Research. You'll see how to enhance a basic prompt by assigning a persona, specifying a table format for the output, and directing the AI to search specific sources like Reddit for richer insights.

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In this video, you'll learn to use an AI assistant to streamline large-scale event planning. You'll see how to prompt an AI to brainstorm off-site ideas, create fair groups for icebreakers, build a shuttle schedule based on arrival times, and analyze survey feedback for gains and losses.

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In this video, you'll learn to use Gemini Deep Research to make complex purchasing decisions with confidence. You'll see how to write a nuanced, personal prompt about your specific needs and receive a synthesized, comparative report that cuts through the clutter of online reviews.

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In this video, you'll learn to turn your study guides into interactive quizzes using Gemini Canvas. You'll see how to upload your notes and use a simple prompt to generate a quiz with multiple choice and fill-in-the-blank questions that provide immediate feedback.

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In this video, you'll learn to use Gemini Deep Research to conduct competitive marketing analysis. You'll see how to submit a research prompt, approve the personalized research plan Gemini creates, and receive a detailed, synthesized report on competitor campaigns to inform your strategy.

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In this video, you'll learn to build a working prototype of a personalized weather app using Gemini Canvas. You'll see how to specify the cities for a 7-day forecast and then use a follow-up prompt to change the app's theme to a minimal, dark mode interface.

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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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In this video, you'll learn to create complex animated art using Gemini Canvas. You'll see how to write a descriptive prompt to generate a kinetic typography animation with distortion effects, and then use a follow-up prompt to completely change its color style.

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In this video, you'll learn to build a reusable, custom "Study Guide Gem." You'll see how to write the core instructions for your Gem once, and then use it again and again to transform messy notes and articles into a perfectly structured study guide with a summary, outline, and glossary.

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In this video, you'll learn to create an interactive 3D simulation using Gemini Canvas. You'll see how to build a 3D model of the solar system from a single sentence and then use follow-up prompts to add interactive and educational features, like clickable planets and fun facts.

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In this video, you'll learn to build a custom personal utility app using Gemini Canvas. You'll see how to write a detailed prompt to create a Pomodoro timer tailored to your specific needs, and then use follow-up prompts to adjust its visual design.

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In this video, you'll learn to use the Guided Learning experience in Gemini to build a deep understanding of any topic. You'll see how to start a conversation, engage with Gemini's probing questions, and use interactive tools like diagrams and quizzes to guide your learning journey.

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In this video, you'll learn to use a simple text prompt in Gemini Canvas to build a playable game. You'll see how to create a Tic-Tac-Toe game, use a follow-up prompt to customize its theme to a retro 8-bit style, and share the final game with a link.

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In this video, you'll learn to build a working music synthesizer using a simple text prompt in Gemini Canvas. You'll see how to specify controls like waveform, attack, and sustain, and then interact with the generated instrument to create and experiment with your own unique sounds.

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In this video, you'll learn to use creative prompts in Gemini to make complex research fun and easy to understand. You'll see how to ask Gemini to research a topic and present the findings in a creative format, like a sports scouting report and a head-to-head bracket, to better visualize and compare your options.

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In this video, you'll learn to use the Create menu in Gemini Canvas to instantly convert a block of text into a variety of visual formats. You’ll see how to take a brainstormed marketing campaign and turn it into both a shareable infographic and an internal webpage with just one click.

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In this video, you'll learn to use Gemini Canvas to turn a simple drawing into a working app. You'll upload a sketch, use a simple prompt to generate code, watch a live preview build itself, and make iterative changes to your app prototype using natural language.

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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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Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities. This course teaches you to use Generative AI App Builder to integrate enterprise-grade generative AI search.

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Specifically designed for healthcare professionals, this course demystifies generative AI, the latest breakthrough in artificial intelligence, and the large language models (LLMs) that drive it. Discover real-world applications of generative AI in healthcare settings and master the art of crafting effective prompts tailored to your goals.

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In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.

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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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AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.

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Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.

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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.

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Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.

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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.

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Complete the introductory Get Started with Sensitive Data Protection skill badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.

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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.

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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.

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AI inference is the process of using a trained machine learning model to make predictions on new, unseen data by applying learned patterns. This course is designed for developers, data scientists, and ML engineers interested in quickly deploying AI inference services on Cloud Run. It is useful for those familiar with cloud-based serverless application deployment solutions, but who may not have experience with running AI inference using Google Cloud serverless products. The course includes examples that deploys a model for AI inference with GPUs and integrates gen AI apps with data storage services.

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This video covers how to create a 'project notebook' in NotebookLM by adding all relevant sources to build a central, searchable knowledge hub for your team.

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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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This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.

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This video covers how to use the Mind Maps feature in NotebookLM to automatically create a visual representation of your sources, helping you understand connections and key concepts.

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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 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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This video covers how to use the 'Help me create' feature in Google Docs to generate a complete, formatted document by referencing content from other files in your Drive.

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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 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 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 to use Gemini and Apps Script to automate manual tasks across Google Workspace. You'll learn to prompt Gemini to generate Apps Script code that automatically drafts email reminders in Google Sheets for tasks not marked 'Complete.' Automate your workflow with little to no technical expertise, freeing up time for more important work and eliminating manual follow-ups.

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AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.

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This video covers how to personalize your Gemini results in Google Workspace. Learn to incorporate documents and research papers directly into your prompts using the "@" symbol to get more targeted and relevant AI output tailored to your needs.

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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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This video will cover how you can leverage Gemini's advanced AI capabilities in Google Docs to brainstorm ideas, draft various marketing content, and collaborate with your team.

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This video covers how to use NotebookLM for common marketing tasks like analyzing customer feedback, conducting market research, and generating content ideas.

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This course is designed for Google Cloud developers and DevOps engineers who have basic knowledge of the Google Cloud console and are responsible for configuring Gemini Code Assist for an organization. The course introduces the benefits of Gemini Code Assist and compares the features of the different Gemini Code Assist editions. The course also shows you how to configure and manage Gemini Code Assist within an organization.

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Ukończ szkolenie wprowadzające Przygotowywanie danych do użycia z interfejsami ML w Google Cloud, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: czyszczenie danych przy użyciu usługi Dataprep firmy Trifacta, uruchamianie potoków danych w Dataflow, tworzenie klastrów i uruchamianie zadań Apache Spark w Dataproc, a także wywoływanie interfejsów API dotyczących uczenia maszynowego, w tym Cloud Natural Language API, Google Cloud Speech-to-Text API oraz Video Intelligence API.

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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.

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This course reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI applications.

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Welcome to the Cloud TPUs course. We'll explore the advantages and disadvantages of TPUs in various scenarios and compare different TPU accelerators to help you choose the right fit. You'll learn strategies to maximize performance and efficiency for your AI models and understand the significance of GPU/TPU interoperability for flexible machine learning workflows. Through engaging content and practical demos, we'll guide you step-by-step in leveraging TPUs effectively.

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Curious about the powerful hardware behind AI? This module breaks down performance-optimized AI computers, showing you why they're so important. We'll explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them. By the end, you'll know exactly how to pick the right GPU for your AI projects, helping you make smart choices for your AI workloads.

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Ready to get started with AI Hypercomputers? This course makes it easy! We'll cover the basics of what they are and how they help AI with AI workloads. You'll learn about the different components inside a hypercomputer, like GPUs, TPUs, and CPUs, and discover how to pick the right deployment approach for your needs.

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Complete the intermediate Analyze and Reason on Multimodal Data with Gemini skill badge course to demonstrate skills in the following: analyzing text, image, audio, and video data using Gemini, and reasoning about this combined information to draw conclusions and extract insights.

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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows. Duet AI was renamed to Gemini, our next-generation model.

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The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.

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Complete the intermediate Explore Generative AI with the Gemini API in Vertex AI skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects.

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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.

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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.

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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

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Gen AI: Navigate the Landscape s the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.

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To szkolenie wprowadza w ważne kwestie dotyczące prywatności i bezpieczeństwa w dziedzinie AI. W jego trakcie przedstawiamy praktyczne techniki i narzędzia, które umożliwiają wdrożenie sprawdzonych metod w zakresie prywatności i bezpieczeństwa AI przy użyciu usług Google Cloud oraz narzędzi open source.

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Na tym szkoleniu przedstawiamy koncepcje interpretowalności i przejrzystości AI. Omawiamy na nim, jak ważna jest przejrzystość AI dla deweloperów i inżynierów. Pokazujemy praktyczne techniki i narzędzia, które pomagają osiągnąć interpretowalność oraz przejrzystość zarówno w danych, jak i modelach AI.

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Na tym szkoleniu przedstawiamy koncepcje odpowiedzialnej AI i zasad dotyczących AI. Omawiamy praktyczne metody identyfikowania obiektywności i uprzedzeń, a także ograniczania występowania uprzedzeń podczas używania AI/ML. W trakcie szkolenia przedstawiamy też praktyczne techniki i narzędzia, które umożliwiają wdrożenie sprawdzonych metod w zakresie odpowiedzialnej AI przy użyciu usług Google Cloud oraz narzędzi open source.

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This video covers how you can leverage Gemini's advanced AI capabilities within Google Sheets to effortlessly pull data and generate insights in minutes, all without the need for any technical or coding background.

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This video will cover how to leverage Gemini Gems to create authentic social media posts in your leader's unique voice. Learn to overcome the challenge of scaling executive social presence by training a Gem with writing samples and clear instructions. Discover how to generate engaging posts quickly, saving time while amplifying thought leadership and ensuring authenticity.

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This video covers how you can create your own Brevity Gem to summarize and transform messy notes or long documents into clear, concise, executive-ready summaries.

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This video covers how you can leverage Notebook LM to "eat the frog" on your to-do list by automating complex tasks like summarizing legislation and mapping services, saving you hours of work.

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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 will cover how to use NotebookLM to gather and analyze publicly available information, combine it with internal documents, and extract key competitive insights.

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This video covers how you can use Gemini to summarize long documents in Google Workspace, so you can quickly get the information you need and save time. You'll learn how to use Gemini to summarize entire documents or just selected text, as well as how to use Gemini in Drive to summarize across multiple files.

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This video covers how NotebookLM can revolutionize customer insight gathering from call or chat transcripts. You'll learn to upload PDF transcripts of hundreds of conversations (even multilingual ones!) and quickly extract key themes, trending topics, and actionable insights without listening for hours. Discover how to save findings, share notebooks, and even generate interactive podcast summaries of your data.

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This video covers how to create your own Gemini Gems, advanced AI capabilities that can automate repetitive tasks and supercharge your productivity.

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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.

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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.

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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.

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Complete the intermediate Enhance Gemini Model Capabilities skill badge to demonstrate skills in the following: leveraging advanced features of Gemini models, including code generation and execution, grounding, controlled content generation, and synthetic data creation, to build more powerful and sophisticated AI applications.

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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Vertex AI platform.

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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud? In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application.

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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini.

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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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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.

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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.

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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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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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Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.

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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 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 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 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 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 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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Aby zdobyć odznakę umiejętności, ukończ szkolenia Introduction to Generative AI, Introduction to Large Language Models i Introduction to Responsible AI. Zdaj test i pokaż, że rozumiesz podstawowe koncepcje związane z generatywną AI. Odznaka umiejętności to cyfrowa odznaka wydawana przez Google Cloud, która potwierdza Twoją wiedzę o produktach i usługach Google Cloud. Ustaw swój profil jako publiczny i dodaj odznakę umiejętności do profilu w mediach społecznościowych, aby pochwalić się swoim osiągnięciem.

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Im szerzej wykorzystuje się w firmach sztuczną inteligencję i systemy uczące się, tym większej wagi nabiera odpowiedzialne podejście do opracowywania tych technologii. Wielu organizacjom trudniej jest jednak wprowadzić zasady odpowiedzialnej AI w praktyce niż tylko o tym rozmawiać. To szkolenie jest przeznaczone dla osób, które chcą się dowiedzieć, jak wdrożyć odpowiedzialną AI w swojej organizacji. W jego trakcie dowiesz się, jak robimy to w Google Cloud, oraz poznasz sprawdzone metody i wnioski z naszych działań w tym zakresie. Pomoże Ci to opracować własne podejście do odpowiedzialnej AI.

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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest odpowiedzialna AI i dlaczego jest ważna, oraz przedstawienie, jak Google wprowadza ją w swoich usługach. Szkolenie zawiera także wprowadzenie do siedmiu zasad Google dotyczących sztucznej inteligencji.

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To szybkie szkolenie dla początkujących wyjaśnia, czym są duże modele językowe (LLM) oraz jakie są ich zastosowania. Przedstawia również możliwości zwiększenia ich wydajności przez dostrajanie przy użyciu promptów oraz narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.

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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest generatywna AI oraz jakie są jej zastosowania. Szkolenie przedstawia również różnice pomiędzy tą technologią a tradycyjnymi systemami uczącymi się, a także narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.

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