Sajo Sam
Member since 2022
Silver League
29160 points
Transformer Models and BERT Model - בעברית
Earned נוב 16, 2023 EST
Encoder-Decoder Architecture - בעברית
Earned נוב 16, 2023 EST
Attention Mechanism - בעברית
Earned נוב 16, 2023 EST
Introduction to Image Generation - בעברית
Earned נוב 16, 2023 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned נוב 15, 2023 EST
Generative AI Fundamentals - בעברית
Earned נוב 15, 2023 EST
Introduction to Responsible AI - בעברית
Earned נוב 15, 2023 EST
Introduction to Large Language Models - בעברית
Earned נוב 15, 2023 EST
Introduction to Generative AI - בעברית
Earned נוב 15, 2023 EST
New Year, New Skills: Yellow Challenge (A)
Earned ינו 6, 2023 EST
New Year, New Skills: Green Challenge (A)
Earned ינו 5, 2023 EST
MongoDB Atlas on Google Cloud
Earned דצמ 15, 2022 EST
[DEPRECATED] Build Interactive Apps with Google Assistant
Earned יונ 18, 2022 EDT
Develop Serverless Apps with Firebase
Earned יונ 18, 2022 EDT
Build Apps & Websites with Firebase
Earned יונ 18, 2022 EDT
Implement DevOps Workflows in Google Cloud
Earned יונ 18, 2022 EDT
Deploy Kubernetes Applications on Google Cloud
Earned יונ 18, 2022 EDT
Use Machine Learning APIs on Google Cloud
Earned יונ 18, 2022 EDT
Workspace: Add-ons
Earned יונ 17, 2022 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned יונ 17, 2022 EDT
Machine Learning APIs
Earned יונ 17, 2022 EDT
DevOps Essentials
Earned יונ 16, 2022 EDT
DEPRECATED Cloud Architecture
Earned יונ 16, 2022 EDT
Google Developer Essentials
Earned יונ 16, 2022 EDT
DEPRECATED Language, Speech, Text, & Translation with Google Cloud APIs
Earned יונ 16, 2022 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned יונ 12, 2022 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned יונ 5, 2022 EDT
Security & Identity Fundamentals
Earned יונ 5, 2022 EDT
Develop Your Google Cloud Network
Earned יונ 4, 2022 EDT
Build a Secure Google Cloud Network
Earned יונ 4, 2022 EDT
Monitor and Log with Google Cloud Observability
Earned יונ 4, 2022 EDT
Implement Cloud Security Fundamentals on Google Cloud
Earned יונ 4, 2022 EDT
Prepare Data for ML APIs on Google Cloud
Earned יונ 4, 2022 EDT
Intro to ML: Image Processing
Earned יונ 4, 2022 EDT
Intro to ML: Language Processing
Earned יונ 4, 2022 EDT
Baseline: Data, ML, AI
Earned יונ 3, 2022 EDT
Cloud Engineering
Earned יונ 1, 2022 EDT
Kubernetes in Google Cloud
Earned יונ 1, 2022 EDT
Set Up an App Dev Environment on Google Cloud
Earned מאי 23, 2022 EDT
DEPRECATED Google Cloud's Operations Suite
Earned מאי 15, 2022 EDT
הבנת העלויות ב-Google Cloud
Earned מאי 13, 2022 EDT
Baseline: Infrastructure
Earned מאי 12, 2022 EDT
Create ML Models with BigQuery ML
Earned מאי 11, 2022 EDT
Build a Data Warehouse with BigQuery
Earned מאי 10, 2022 EDT
Scientific Data Processing
Earned מאי 7, 2022 EDT
Cloud SQL
Earned מאי 7, 2022 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned מאי 7, 2022 EDT
[DEPRECATED] Data Engineering
Earned מאי 7, 2022 EDT
DEPRECATED BigQuery for Data Warehousing
Earned מאי 7, 2022 EDT
Derive Insights from BigQuery Data
Earned מאי 6, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned מאי 6, 2022 EDT
DEPRECATED BigQuery for Marketing Analysts
Earned מאי 4, 2022 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned מאי 2, 2022 EDT
DEPRECATED Applied Data: Blockchain
Earned מאי 1, 2022 EDT
BigQuery for Machine Learning
Earned אפר 28, 2022 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned אפר 26, 2022 EDT
Google Cloud Essentials
Earned אפר 26, 2022 EDT
Understanding Google Cloud Security and Operations - בעברית
Earned ינו 31, 2022 EST
Infrastructure and Application Modernization with Google Cloud - בעברית
Earned ינו 31, 2022 EST
Innovating with Data and Google Cloud - בעברית
Earned ינו 30, 2022 EST
Digital Transformation with Google Cloud - בעברית
Earned ינו 30, 2022 EST
Implementing Cloud Load Balancing for Compute Engine
Earned ינו 30, 2022 EST
Learn to Earn Cloud Security Challenge: Level 2
Earned ינו 20, 2022 EST
Learn to Earn Cloud Security Challenge: Level 1
Earned ינו 18, 2022 EST
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 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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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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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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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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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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New year, New skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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Discover the ease of an integrated multi-cloud database with data services that simplify database deployment and management. Get practical experience using MongoDB Atlas on Google Cloud and unlock the power of a flexible document data model that makes data easier to work with in a global, scalable, fully-managed, and elastic service. Come expecting to learn, Building a Cloud Run application that leverages Atlas App Services to call Cloud Natural Language Processing and carry out sentiment analysis, Running a MongoDB Database in Kubernetes with StatefulSets and Ingesting New Datasets into BigQuery
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Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. 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 the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Complete the intermediate Develop Serverless Apps with Firebase skill badge course to demonstrate skills in the following: architecting and building serverless web applications with Firebase, utilizing Firestore for database management, automating deployment processes using Cloud Build, and integrating Google Assistant functionality into your applications.
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Firebase is a backend-as-service (Bass) platform for creating mobile and web applications. In this quest you will learn to build serverless web apps, import data into a serverless database, and build a Google Assistant application with Firebase and its Google Cloud integrations. 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 this quest to receive an exclusive Google Cloud digital badge.
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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating and managing Git 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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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 demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.
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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.
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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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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this course you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out!
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This fundamental-level quest is unique amongst the other quest 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 Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
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In this quest you will use a collection of Google APIs that are all related to language, and speech. You will use the Speech-to-Text API to transcribe an audio file into a text file, the Cloud Translation API to translate from one language to another, the Cloud Translation API to detect what language is being used and translate to a different language, the Natural Language API to classify text and analyze sentiment, and create synthetic speech.
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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.
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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.
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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.
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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.
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Earn a skill badge by completing the Build a Secure Google Cloud Network skill badge course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud.
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Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.
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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
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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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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like BigQuery, Cloud Speech API and Video Intelligence. Want extra help? 1-minute videos walk you through key concepts for each lab.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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Learn the ins and outs of Google Cloud's operations suite, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. These labs will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.
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המשימה הזו מתאימה במיוחד לבעלי תפקידים בתחומי הטכנולוגיה או הפיננסים, שאחראים לניהול של העלויות ב-Google Cloud. תלמדו איך להגדיר חשבון חיוב, איך לארגן משאבים ואיך לנהל הרשאות גישה לחיוב. בשיעורים המעשיים האלה תלמדו איך להציג את החשבונית, לנתח את נתוני החיוב באמצעות BigQuery או Google Sheets וליצור מרכזי בקרה לחיוב בהתאמה אישית באמצעות Data Studio.
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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.
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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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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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Big data, machine learning, and scientific data? It sounds like the perfect match. In this course, you will get hands-on practice with GCP services like BigQuery, Managed Service for Apache Spark, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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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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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. 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. 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 this quest to receive an exclusive Google Cloud digital badge.
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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 Data Studio by connecting to BigQuery data.
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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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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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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
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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 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.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
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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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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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These labs will give you a deeper understanding of security features in the cloud. These labs are a little more challenging. It’s OK to take a lab more than once to achieve a great score. Complete this game to earn the Level 2 game badge, and you'll be one step closer to completing the challenge. Race the clock to increase your score and watch your name rise on the leaderboard!
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These labs help you get started with cloud security basics. At the end of each lab, you'll have hands-on experience with securing your cloud. Complete this game to earn the Level 1 game badge, and you'll be one step closer to completing the challenge. Race the clock to increase your score and watch your name rise on the leaderboard!
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