M SREE KAMESWARI SNEHA
Jest członkiem od 2024
Liga brązowa
15267 pkt.
Introduction to Image Generation
Earned mar 22, 2026 EDT
Odpowiedzialna AI dla deweloperów: obiektywność i uprzedzenia
Earned lut 27, 2026 EST
Arcade Trail: Application Development
Earned lut 26, 2026 EST
From Foundations To Wonders
Earned lut 25, 2026 EST
Gen AI: Navigate the Landscape
Earned lut 25, 2026 EST
Gen AI: Beyond the Chatbot
Earned lut 25, 2026 EST
Gen AI: Unlock Foundational Concepts
Earned lut 25, 2026 EST
Gen AI Apps: Transform Your Work
Earned lut 25, 2026 EST
Build a Certification Study Guide: PSOE Exam Prep
Earned lut 25, 2026 EST
Arcade February 2026 Sprint 4
Earned lut 25, 2026 EST
Arcade February 2026 Sprint 3
Earned lut 25, 2026 EST
Arcade February 2026 Sprint 2
Earned lut 24, 2026 EST
Arcade February 2026 Sprint 1
Earned lut 24, 2026 EST
Skills At The Pitch
Earned lut 24, 2026 EST
Google DeepMind: 01 Build Your Own Small Language Model
Earned lut 24, 2026 EST
Deploy and Scale AI Models with Cloud Run
Earned lut 23, 2026 EST
Configure Gemini Code Assist for Organizations
Earned lut 23, 2026 EST
Gemini for end-to-end SDLC
Earned lut 23, 2026 EST
Introduction to Responsible AI - Polski
Earned lut 22, 2026 EST
Responsible AI: Applying AI Principles with Google Cloud - Polski
Earned lut 22, 2026 EST
Introduction to Large Language Models - Polski
Earned lut 22, 2026 EST
Introduction to Generative AI - Polski
Earned lut 22, 2026 EST
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation
Earned lut 21, 2026 EST
Machine Learning Operations (MLOps) for Generative AI
Earned lut 21, 2026 EST
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 Gemini Enterprise Agent Platform.
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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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Developers using managed cloud services can reduce infrastructure management effort by up to 60%, allowing more time to focus on building features that matter. In this level, you’ll gain hands-on experience with Cloud SQL, containerized workloads, and cloud-native application development through the Arcade ACE App Dev series, helping you design, deploy, and manage scalable applications more efficiently.
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As Pup and Kit move through the city between matches—booking plans on the fly, exploring structures built to last, and navigating busy streets—the story reflects what it takes to keep systems running smoothly behind the scenes. From securing storage and shaping networks to improving performance, reliability, and cost efficiency, these labs echo the quiet work that makes flexibility possible. Along the way, hands-on challenges and quizzes sharpen decision-making, so when it’s time for the next big play, everything is ready to perform.
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Gen AI: Navigate the Landscape is 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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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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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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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 Gemini Notebook. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Security Operations Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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This month's Arcade Sprint 4 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!
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This month's Arcade Sprint 3 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!
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This month's Arcade Sprint 2 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!
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This month's Arcade Sprint 1 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!
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Pup and Kit’s World Cup journey highlights how the right skills quietly power great experiences. As they plan, adapt, and stay in sync using data, automation, and cloud-based tools, the story nudges you to step into their shoes and build those capabilities yourself. Each lab mirrors a moment from their adventure, encouraging you to explore, experiment, and strengthen skills that help you stay prepared, move faster, and make smarter choices-whatever the situation demands.
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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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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 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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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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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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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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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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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 Agent Platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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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 Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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