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Google Cloud Skills Boost

Apply your skills in Google Cloud console

Ayesha Iftikhar

Jest członkiem od 2023

Liga diamentowa

33385 pkt.
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG Earned cze 28, 2024 EDT
Responsible AI for Developers: Interpretability & Transparency - Polski Earned cze 27, 2024 EDT
Configure and Maintain CCAIP as an Admin Earned cze 27, 2024 EDT
Vector Search and Embeddings Earned cze 26, 2024 EDT
Manage Functions and Reporting with CCAIP Earned cze 23, 2024 EDT
Handle Consumer Interactions with CCAIP Earned cze 21, 2024 EDT
Gemini in Google Meet Earned cze 20, 2024 EDT
Gemini in Google Sheets Earned cze 20, 2024 EDT
Gemini in Google Slides Earned cze 20, 2024 EDT
Gemini in Google Docs Earned cze 20, 2024 EDT
Gemini in Gmail Earned cze 20, 2024 EDT
Introduction to Gemini for Google Workspace Earned cze 20, 2024 EDT
Conversational AI on Vertex AI and Dialogflow CX Earned cze 19, 2024 EDT
Gemini for Security Engineers Earned cze 19, 2024 EDT
Gemini for end-to-end SDLC Earned cze 19, 2024 EDT
Introduction to Data Analytics on Google Cloud Earned cze 19, 2024 EDT
Customer Experience with Google AI Architecture Earned cze 12, 2024 EDT
Conversational AI telephony and chat integrations Earned cze 12, 2024 EDT
Virtual FAQ with data store agents Earned cze 12, 2024 EDT
DFCX Virtual Agent Delivery Framework Earned cze 11, 2024 EDT
Webhook fundamentals Earned cze 11, 2024 EDT
Gemini for Cloud Architects Earned cze 4, 2024 EDT
Responsible AI for Developers: Fairness & Bias - Polski Earned cze 4, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI Earned cze 4, 2024 EDT
Introduction to Vertex AI Studio Earned cze 4, 2024 EDT
Create Image Captioning Models Earned cze 4, 2024 EDT
Transformer Models and BERT Model Earned cze 3, 2024 EDT
Encoder-Decoder Architecture Earned cze 3, 2024 EDT
Attention Mechanism Earned cze 3, 2024 EDT
Introduction to Image Generation Earned cze 3, 2024 EDT
Prompt Design in Vertex AI Earned maj 30, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud - Polski Earned maj 29, 2024 EDT
Introduction to Responsible AI - Polski Earned maj 27, 2024 EDT
Introduction to Large Language Models - Polski Earned maj 27, 2024 EDT
Introduction to Generative AI - Polski Earned maj 26, 2024 EDT

Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge 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. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course and the final assessment challenge lab to receive a skill badge that you can share with your network.

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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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Configure and Maintain CCAIP as an Admin is a course that provides end users with essential learning about the core features, functionality, reporting, and configuration information most relevant to the role. This course is most appropriate for those who perform administrative functions to support the operation of the contact center as well as analyze, troubleshoot, and configure the platform to best meet the demands of customers. While this program will review some monitoring and reporting aspects, those topics are explored in depth in the course titled, “Managing Functions and Reporting with CCAIP.”

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This course introduces Vertex AI Vector Search and describes how it can be used to build a search application with large language model (LLM) APIs for embeddings. The course consists of conceptual lessons on vector search and text embeddings, practical demos on how to build vector search on Vertex AI, and a hands-on lab.

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Manage Functions and Reporting with CCAI Platform provides end-users with essential training about the core features, functionality, monitoring, reporting, and configuration information that is most relevant to the role. This course is most appropriate for those at the managerial level of the contact center who are tasked with monitoring the effectiveness, efficiency, and KPI attainment for all consumer interactions. While this program will review some aspects of settings and configuration options, the major focus is on reporting functionality in CCAI Platform.

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This course teaches contact center agents about the core agent features and functionality in Contact Center AI Platform (CCAIP). CCAIP is a unified contact center platform that accelerates an organization's ability to leverage and deploy CCAI without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.

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Gemini for Google Workspace provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Meet. Through video lessons, hands-on activities and practical examples, you will gain a comprehensive understanding of the Gemini features in Google Meet. You learn how to use Gemini to generate background images, improve your video quality, and translate captions. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Meet to maximize the effectiveness of your video conferences.

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

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

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Gemini for Google Workspace provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Docs using video lessons, hands-on activities and practical examples. You learn how to use Gemini to generate written content based on prompts. You also explore using Gemini to edit text you’ve already written, helping you improve your overall productivity. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Docs to improve your writing.

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

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Gemini for Google Workspace 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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In this course you will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture. Duet AI was renamed to Gemini, our next-generation model.

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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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In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.

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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX and CCAI Insights.

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This course explores how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem

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In this course, you will learn how to develop a generative agent capable of answering questions from websites, documents, and/or unstructured data. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.

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This course explores the best practices, methods and tools to programmatically lead CCAI virtual agent delivery. It includes a high level overview of the end to end journey for building and deploying a virtual agent, as well as the core tenets to create a strong delivery culture. Additionally, this course covers the best practices for workflow management, defect tracking, release management and post-release support to ensure optimal virtual agent performance.

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In this course, you will learn the important role that different types of webhooks play in Conversational Agents development, and how to effectively integrate them into your routine configuration of a Conversational Agent. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow. Duet AI was renamed to Gemini, our next-generation model.

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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 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 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 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 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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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. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course and the final assessment challenge lab to receive a skill badge that you can share with your network.

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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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