Put It All Together: Prepare for a Cloud Data Analyst Job
Earned יול 19, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned יול 15, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned יול 15, 2024 EDT
Introduction to Image Generation - בעברית
Earned יול 15, 2024 EDT
Level 3: GenAIus Travels
Earned יונ 20, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned יונ 15, 2024 EDT
Exploring and Preparing your Data with BigQuery
Earned יונ 15, 2024 EDT
Trust and Security with Google Cloud
Earned ינו 25, 2024 EST
Innovating with Google Cloud Artificial Intelligence
Earned ינו 25, 2024 EST
Use Machine Learning APIs on Google Cloud
Earned נוב 12, 2023 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned נוב 1, 2023 EDT
Generative AI Fundamentals - בעברית
Earned נוב 1, 2023 EDT
Introduction to Responsible AI - בעברית
Earned נוב 1, 2023 EDT
Introduction to Large Language Models - בעברית
Earned נוב 1, 2023 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned ספט 3, 2023 EDT
[DEPRECATED] Data Engineering
Earned ספט 3, 2023 EDT
Introduction to Generative AI - בעברית
Earned אוג 30, 2023 EDT
Level 3: GenAI
Earned אוג 30, 2023 EDT
Understanding Google Cloud Security and Operations - בעברית
Earned אוג 6, 2023 EDT
Infrastructure and Application Modernization with Google Cloud - בעברית
Earned אוג 6, 2023 EDT
Innovating with Data and Google Cloud - בעברית
Earned אפר 7, 2023 EDT
Digital Transformation with Google Cloud - בעברית
Earned אפר 2, 2023 EDT
Advanced ML: ML Infrastructure
Earned פבר 7, 2021 EST
Intro to ML: Language Processing
Earned ינו 2, 2021 EST
Machine Learning APIs
Earned ינו 1, 2021 EST
Create ML Models with BigQuery ML
Earned דצמ 28, 2020 EST
BigQuery for Machine Learning
Earned דצמ 27, 2020 EST
DEPRECATED BigQuery for Marketing Analysts
Earned דצמ 25, 2020 EST
Derive Insights from BigQuery Data
Earned דצמ 5, 2020 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned דצמ 5, 2020 EST
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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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 introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
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Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.
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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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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 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: 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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בקורס הזה נציג את הארכיטקטורה של טרנספורמרים ואת המודל של ייצוגים דו-כיווניים של מקודד מטרנספורמרים (BERT). תלמדו על החלקים השונים בארכיטקטורת הטרנספורמר, כמו מנגנון תשומת הלב, ועל התפקיד שלו בבניית מודל BERT. תלמדו גם על המשימות השונות שאפשר להשתמש ב-BERT כדי לבצע אותן, כמו סיווג טקסטים, מענה על שאלות והֶקֵּשׁ משפה טבעית. נדרשות כ-45 דקות כדי להשלים את הקורס הזה.
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בקורס הזה תלמדו איך ליצור מודל הוספת כיתוב לתמונה באמצעות למידה עמוקה (Deep Learning). אתם תלמדו על הרכיבים השונים במודל הוספת כיתוב לתמונה, כמו המקודד והמפענח, ואיך לאמן את המודל ולהעריך את הביצועים שלו. בסוף הקורס תוכלו ליצור מודלים להוספת כיתוב לתמונה ולהשתמש בהם כדי ליצור כיתובים לתמונות
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This Course is utilized to certify completion of The Skills Challenge at Next 2025.
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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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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.
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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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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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This is the third of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll begin by getting an overview of the data journey, from collection to insights. You’ll then learn how to use SQL to transform raw data into a usable format. Next, you’ll learn how to transform high volumes of data with a data pipeline. Finally, you’ll gain experience applying transformation strategies to real data sets to solve business needs.
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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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בקורס נלמד על מנגנון תשומת הלב, שיטה טובה מאוד שמאפשרת לרשתות נוירונים להתמקד בחלקים ספציפיים ברצף הקלט. נלמד איך עובד העיקרון של תשומת הלב, ואיך אפשר להשתמש בו כדי לשפר את הביצועים במגוון משימות של למידת מכונה, כולל תרגום אוטומטי, סיכום טקסט ומענה לשאלות.
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This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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This course explores the foundational principles of conversation design to craft engaging and effective chatbot experiences that emulate human-like experiences.
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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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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
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Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.
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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps.
We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views.
After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.
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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series.
In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area.
You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training.
This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.
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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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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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Google Workspace with Gemini 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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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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In this course, you will learn the important role that different types of webhooks play in Dialogflow CX development, and how to effectively integrate them into your routine configuration of a Virtual Agent.
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Google Workspace with Gemini 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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Google Workspace with Gemini 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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Google Workspace with Gemini 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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Google Workspace with Gemini 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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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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In this course you will learn how Contact Center AI Agent Assist can help distill complex customer interactions into concise and clear summaries.
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בקורס הזה לומדים בקצרה על ארכיטקטורת מקודד-מפענח, ארכיטקטורה עוצמתית ונפוצה ללמידת מכונה שמשתמשים בה במשימות של רצף לרצף, כמו תרגום אוטומטי, סיכום טקסט ומענה לשאלות. תלמדו על החלקים השונים בארכיטקטורת מקודד-מפענח, איך לאמן את המודלים האלה ואיך להשתמש בהם. בהדרכה המפורטת המשלימה בשיעור ה-Lab תקודדו ב-TensorFlow תרחיש שימוש פשוט בארכיטקטורת מקודד-מפענח: כתיבת שיר מאפס.
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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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בקורס הזה נלמד על Generative AI Studio, מוצר ב-Vertex AI שעוזר ליצור אבות טיפוס למודלים של בינה מלאכותית גנרטיבית, כדי להשתמש בהם ולהתאים אותם לפי הצרכים שלכם. באמצעות הדגמה של המוצר עצמו, נלמד מהו Generative AI Studio, מהם הפיצ'רים והאפשרויות שלו, ואיך להשתמש בו. בסוף הקורס יהיה שיעור Lab מעשי לתרגול של מה שנלמד, ובוחן לבדיקת הידע.
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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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This is the fifth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll combine and apply the foundational knowledge and skills from courses 1-4 in a hands-on Capstone project that focuses on the full data lifecycle project. You’ll practice using cloud-based tools to acquire, store, process, analyze, visualize, and communicate data insights effectively. By the end of the course, you’ll have completed a project demonstrating their proficiency in effectively structuring data from multiple sources, presenting solutions to varied stakeholders, and visualizing data insights using cloud-based software. You’ll also update your resume and practice interview techniques to help prepare for applying and interviewing for jobs.
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This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
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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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בקורס נלמד על מודלים של דיפוזיה, משפחת מודלים של למידת מכונה שיצרו הרבה ציפיות לאחרונה בתחום של יצירת תמונות. מודלים של דיפוזיה שואבים השראה מפיזיקה, וספציפית מתרמודינמיקה. בשנים האחרונות, מודלים של דיפוזיה הפכו לפופולריים גם בתחום המחקר וגם בתעשייה. מודלים של דיפוזיה עומדים מאחורי הרבה מהכלים והמודלים החדשניים ליצירת תמונות ב-Google Cloud. בקורס הזה נלמד על התיאוריה שמאחורי מודלים של דיפוזיה, ואיך לאמן ולפרוס אותם ב-Vertex AI.
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Excited to follow your favorite soccer/football stars on their next quest? Use GenAIus Travel Guides to learn how to interact with chat applications, master prompt engineering, understand the importance of context in AI, and work with Generative AI. Earn an exclusive Google Cloud Generative AI Credential and showcase your new skills! No prior experience needed!
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets.
This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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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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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
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רוצים לקבל תג מיומנות? אפשר להשלים את הקורסים Introduction to Generative AI, Introduction to Large Language Models ו-Introduction to Responsible AI. מעבר של המבחן המסכם מוכיח שהבנתם את המושגים הבסיסיים בבינה מלאכותית גנרטיבית.
'תג מיומנות' הוא תג דיגיטלי ש-Google מנפיקה, שמוכיח שאתם מכירים את המוצרים והשירותים של Google Cloud. כדי לשתף את תג המיומנות אפשר להפוך את הפרופיל שלכם לגלוי לכולם ולהוסיף אותו לפרופיל שלכם ברשתות חברתיות.
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זהו קורס מבוא ממוקד שמטרתו להסביר מהי אתיקה של בינה מלאכותית, למה היא חשובה ואיך Google נוהגת לפי כללי האתיקה של הבינה המלאכותית במוצרים שלה. מוצגים בו גם 7 עקרונות ה-AI של Google.
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זהו קורס מבוא ממוקד שבוחן מהם מודלים גדולים של שפה (LLM), איך משתמשים בהם בתרחישים שונים לדוגמה ואיך אפשר לשפר את הביצועים שלהם באמצעות כוונון של הנחיות. הוא גם כולל הסבר על הכלים של Google שיעזרו לכם לפתח אפליקציות בינה מלאכותית גנרטיבית משלכם.
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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.
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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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זהו קורס מבוא ממוקד שמטרתו להסביר מהי בינה מלאכותית גנרטיבית, איך משתמשים בה ובמה היא שונה משיטות מסורתיות של למידת מכונה. הוא גם כולל הסבר על הכלים של Google שיעזרו לכם לפתח אפליקציות בינה מלאכותית גנרטיבית משלכם.
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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!
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הקורס בוחן ניהול עלויות, אבטחה ותפעול בענן. ראשית, מוסבר איך עסקים יכולים לרכוש שירותי IT מספק שירותי ענן ולשמר חלק מהתשתית שלהם או לבחור לא לשמר אותה בכלל. שנית, הקורס מתאר איך האחריות על אבטחת נתונים מתחלקת בין ספק שירותי הענן לעסק, וסוקר את אבטחת ההגנה לעומק (defense-in-depth) שמובנית ב-Google Cloud. לבסוף, הקורס מתייחס לכך שצוותי IT ומנהלי העסק צריכים לשנות את החשיבה על ניהול משאבי IT בענן, ונוגע באופן שבו כלי ניטור המשאבים ב-Google Cloud יכולים לסייע להם לשמור על שליטה וניראות בסביבת הענן שלהם.
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בארגונים מסורתיים רבים משתמשים במערכות ובאפליקציות מדורות קודמים, וקשה לבצע באמצעותן התאמה לעומס ופעולות מהירות הדרושות כדי לעמוד בציפיות מודרניות של לקוחות. מנהיגים עסקיים וקובעי מדיניות IT צריכים כל הזמן לבחור בין תחזוקה של מערכות מדורות קודמים לבין השקעה במוצרים ובשירותים חדשים.
בקורס הזה נבחן את האתגרים הנובעים משימוש בתשתית IT מיושנת, ואיך בעלי עסקים יכולים לבצע מודרניזציה של תשתיות בעזרת טכנולוגיית ענן. הקורס מתחיל בהבנה מעמיקה של אפשרויות המחשוב השונות הזמינות בענן ופירוט היתרונות של כל אחת מהאפשרויות. לאחר מכן נבחן את האפשרויות למודרניזציה של האפליקציות ושל ממשקי API (ממשק תכנות יישומים). בקורס מתוארים גם מגוון פתרונות של Google Cloud שיכולים לשפר את תהליך פיתוח המערכות וניהולן בעסקים שונים, כמו Compute Engine, App Engine ו-Apigee.
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טכנולוגיית הענן לבדה מספקת לעסק חלק קטן בלבד מהערך האמיתי שלה. כשהיא משולבת עם נתונים בנפח רב מאוד, נוצרת העוצמה שמאפשרת להפיק ערך וליצור חוויות חדשות ללקוחות.
במסגרת הקורס הזה תלמדו מהם נתונים, איך השתמשו בהם בעבר בחברות לצורך קבלת החלטות ולמה הם קריטיים כל כך ללמידה חישובית. בנוסף, בקורס הזה יוצגו ללומדים מושגים טכניים כמו נתונים מובְנים ולא מובְנים, מסד נתונים, מחסן נתונים (data warehouse) ואגמי נתונים (data lakes). בהמשך, הקורס יעסוק במוצרי Google Cloud הנפוצים ביותר בתחום הנתונים, ובמוצרים כאלה ששיעור השימוש בהם גדל במהירות הרבה ביותר.
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מהי טכנולוגיית ענן ומהו מדע הנתונים? וחשוב יותר, איך הם יכולים לעזור לכם, לצוות שלכם ולעסק שלכם?
קורס המבוא הזה בנושא טרנספורמציה דיגיטלית מתאים למי שרוצה ללמוד על טכנולוגיית הענן כדי להתמקצע ולהצטיין בעבודתו וכדי לעזור בפיתוח העתיד של העסק.
בקורס יוגדרו מונחי יסוד כגון הענן, נתונים וטרנספורמציה דיגיטלית. בנוסף, נבחן דוגמאות של חברות מרחבי העולם שמשתמשות בטכנולוגיית הענן כדי לבצע טרנספורמציה בעסק. הקורס כולל סקירה של סוגי ההזדמנויות שיש לחברות ושל האתגרים הנפוצים שחברות מתמודדות איתם במהלך טרנספורמציה דיגיטלית. הקורס גם מדגים איך עמודי התווך של פתרונות Google Cloud יכולים לעזור בתהליך. חשוב לומר: טרנספורמציה דיגיטלית לא קשורה רק לשימוש בטכנולוגיות חדשות. כדי הטרנספורמציה תהיה מלאה, ארגונים צריכים גם ליישם חדשנות ולפתח דפוס חשיבה שמקדם חדשנות בכל התחומים והצוותים. השיטות המומלצות המתוארות בקורס יעזרו לכם להשיג את המטרה הזו.
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Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on Google Cloud.
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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory course, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.
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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model.
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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Looker Studio by connecting to BigQuery data.
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Gen AI Agents: Transform Your Organization
Earned אוק 1, 2025 EDT
Introduction to Security in the World of AI
Earned אוג 9, 2025 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned אוג 9, 2025 EDT
Using BigQuery Machine Learning for Inference
Earned אוג 9, 2025 EDT
AI Boost Bites: TL;DR with Gemini in Docs & Drive
Earned יונ 19, 2025 EDT
AI Boost Bites: Customer insights with NotebookLM
Earned יונ 19, 2025 EDT
AI Boost Bites: Gemini Gems – Your ultimate marketing sidekick
Earned יונ 19, 2025 EDT
Gen AI Apps: Transform Your Work
Earned יונ 19, 2025 EDT
Gen AI: Navigate the Landscape
Earned יונ 17, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned יונ 16, 2025 EDT
Gen AI: Beyond the Chatbot
Earned יונ 13, 2025 EDT
Transformer Models and BERT Model - בעברית
Earned יונ 9, 2025 EDT
Create Image Captioning Models - בעברית
Earned יונ 9, 2025 EDT
The Skills Challenge at Next 2025
Earned מרץ 16, 2025 EDT
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned מרץ 3, 2025 EST
Introduction to Data Analytics in Google Cloud
Earned פבר 21, 2025 EST
Gemini for Data Scientists and Analysts
Earned פבר 14, 2025 EST
Vector Search and Embeddings
Earned פבר 14, 2025 EST
Data Transformation in the Cloud
Earned פבר 11, 2025 EST
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned ינו 26, 2025 EST
Attention Mechanism - בעברית
Earned אוק 25, 2024 EDT
Professional Machine Learning Engineer Study Guide
Earned אוק 23, 2024 EDT
Conversation Design Fundamentals
Earned אוק 23, 2024 EDT
Introduction to Data Analytics on Google Cloud
Earned אוק 23, 2024 EDT
Work with Gemini Models in BigQuery
Earned אוק 22, 2024 EDT
Data Lake Modernization on Google Cloud: Cloud Composer
Earned אוק 11, 2024 EDT
Achieving Advanced Insights with BigQuery
Earned אוק 5, 2024 EDT
DEPRECATED Planning for a Google Workspace Deployment
Earned אוג 17, 2024 EDT
Prompt Design in Vertex AI
Earned אוג 16, 2024 EDT
Launching into Machine Learning
Earned אוג 14, 2024 EDT
Responsible AI for Developers: Fairness & Bias
Earned אוג 14, 2024 EDT
Gemini for Application Developers
Earned אוג 14, 2024 EDT
Gemini in Google Slides
Earned אוג 12, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned יול 30, 2024 EDT
Webhook fundamentals
Earned יול 29, 2024 EDT
Gemini in Google Meet
Earned יול 28, 2024 EDT
Gemini in Google Sheets
Earned יול 26, 2024 EDT
Gemini in Gmail
Earned יול 26, 2024 EDT
Gemini in Google Docs
Earned יול 26, 2024 EDT
Introduction to Google Workspace with Gemini
Earned יול 26, 2024 EDT
Agent Summarization (Custom)
Earned יול 26, 2024 EDT
Encoder-Decoder Architecture - בעברית
Earned יול 26, 2024 EDT
Gemini for end-to-end SDLC
Earned יול 26, 2024 EDT
Introduction to Generative AI Studio - בעברית
Earned יול 25, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned יול 24, 2024 EDT
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned יול 19, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned יול 15, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned יול 15, 2024 EDT
Introduction to Image Generation - בעברית
Earned יול 15, 2024 EDT
Level 3: GenAIus Travels
Earned יונ 20, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned יונ 15, 2024 EDT
Exploring and Preparing your Data with BigQuery
Earned יונ 15, 2024 EDT
Trust and Security with Google Cloud
Earned ינו 25, 2024 EST
Innovating with Google Cloud Artificial Intelligence
Earned ינו 25, 2024 EST
Use Machine Learning APIs on Google Cloud
Earned נוב 12, 2023 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned נוב 1, 2023 EDT
Generative AI Fundamentals - בעברית
Earned נוב 1, 2023 EDT
Introduction to Responsible AI - בעברית
Earned נוב 1, 2023 EDT
Introduction to Large Language Models - בעברית
Earned נוב 1, 2023 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned ספט 3, 2023 EDT
[DEPRECATED] Data Engineering
Earned ספט 3, 2023 EDT
Introduction to Generative AI - בעברית
Earned אוג 30, 2023 EDT
Level 3: GenAI
Earned אוג 30, 2023 EDT
Understanding Google Cloud Security and Operations - בעברית
Earned אוג 6, 2023 EDT
Infrastructure and Application Modernization with Google Cloud - בעברית
Earned אוג 6, 2023 EDT
Innovating with Data and Google Cloud - בעברית
Earned אפר 7, 2023 EDT
Digital Transformation with Google Cloud - בעברית
Earned אפר 2, 2023 EDT
Advanced ML: ML Infrastructure
Earned פבר 7, 2021 EST
Intro to ML: Language Processing
Earned ינו 2, 2021 EST
Machine Learning APIs
Earned ינו 1, 2021 EST
Create ML Models with BigQuery ML
Earned דצמ 28, 2020 EST
BigQuery for Machine Learning
Earned דצמ 27, 2020 EST
DEPRECATED BigQuery for Marketing Analysts
Earned דצמ 25, 2020 EST
Derive Insights from BigQuery Data
Earned דצמ 5, 2020 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned דצמ 5, 2020 EST