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Jared Parr

회원 가입일: 2024

다이아몬드 리그

141675포인트
Extends to Keep LookML DRY Earned 2월 10, 2025 EST
Migrating VMware to Google Cloud VMware Engine Earned 2월 2, 2025 EST
Serverless Data Processing with Dataflow: Develop Pipelines Earned 2월 1, 2025 EST
Webhook fundamentals Earned 2월 1, 2025 EST
Conversation Design Fundamentals Earned 2월 1, 2025 EST
Advanced Performance Measurement Earned 2월 1, 2025 EST
Workspace Transformation Earned 2월 1, 2025 EST
Analytics for SAP on Google Cloud Earned 1월 23, 2025 EST
Google Drive의 Gemini Earned 1월 15, 2025 EST
Google Meet의 Gemini Earned 1월 15, 2025 EST
Google Slides의 Gemini Earned 1월 15, 2025 EST
Google Vids로 멋진 동영상 만들기 Earned 1월 15, 2025 EST
Snowflake to BigQuery Migration Earned 12월 31, 2024 EST
Inside Track: DORA Earned 12월 31, 2024 EST
Managing Change for Google Workspace Earned 12월 31, 2024 EST
DFCX Virtual Agent Delivery Framework Earned 12월 30, 2024 EST
Intro to Conversational AI and Conversational AI Engagement Framework Earned 12월 30, 2024 EST
Google Docs의 Gemini Earned 12월 30, 2024 EST
Partner Pre-Sales Readiness Training Earned 12월 30, 2024 EST
Security Practices with Google Security Operations - SIEM Earned 12월 29, 2024 EST
Google Security Operations - Fundamentals Earned 12월 29, 2024 EST
DEPRECATED Google Threat Intelligence Earned 12월 29, 2024 EST
Quiz: GDC Air-Gapped Security Operator Fundamentals Earned 12월 23, 2024 EST
SecOps on GDC for Tier 1 and Tier 2 Analysts Earned 12월 23, 2024 EST
Introduction to Security in the World of AI Earned 12월 22, 2024 EST
Vertex AI로 머신러닝 작업(MLOps): 모델 평가 Earned 12월 22, 2024 EST
Delivery Navigator for Partners Earned 12월 19, 2024 EST
Data Warehousing for Partners: Enable Google Cloud Customers Earned 12월 19, 2024 EST
Elastic Cloud Infrastructure: Scaling and Automation Earned 12월 14, 2024 EST
Accelerate Your Creativity with Text-to-Image using Imagen Earned 12월 13, 2024 EST
SecOps on GDC for Tier 3 Analysts Earned 12월 13, 2024 EST
Google Cloud: Prompt Engineering Guide Earned 12월 13, 2024 EST
SOAR Fundamentals Earned 12월 12, 2024 EST
Cloud Foundations: Customer Onboarding Best Practices Earned 12월 11, 2024 EST
Scaling with Google Cloud Operations Earned 11월 30, 2024 EST
Trust and Security with Google Cloud Earned 11월 30, 2024 EST
Rapid Migration & Modernization Program Earned 11월 30, 2024 EST
Modernize Infrastructure and Applications with Google Cloud Earned 11월 29, 2024 EST
Migrating Backing Up and Disaster Recovery in Google Cloud VMware Engine Earned 11월 9, 2024 EST
Serverless Data Processing with Dataflow: Operations Earned 11월 9, 2024 EST
Serverless Data Processing with Dataflow: Foundations Earned 11월 8, 2024 EST
Implementing Generative AI with Vertex AI Earned 11월 1, 2024 EDT
Generative AI for Business Leaders Earned 11월 1, 2024 EDT
Google Security Operations - SOAR Analyst Earned 10월 26, 2024 EDT
Teradata to BigQuery Earned 10월 25, 2024 EDT
Preparing for your Professional Data Engineer Journey Earned 10월 25, 2024 EDT
Modernizing Mainframe Applications with Google Cloud Earned 10월 23, 2024 EDT
PostgreSQL to Cloud SQL Earned 10월 23, 2024 EDT
VM Migration for Partners Earned 10월 23, 2024 EDT
Cloudera to Google Cloud Earned 10월 23, 2024 EDT
Microsoft SQL Server to Cloud SQL Earned 10월 23, 2024 EDT
MySQL to Cloud Spanner Earned 10월 23, 2024 EDT
MySQL to Cloud SQL Earned 10월 23, 2024 EDT
PostgreSQL to AlloyDB Earned 10월 23, 2024 EDT
Redshift to BigQuery Earned 10월 23, 2024 EDT
BigQuery Migration Service Earned 10월 23, 2024 EDT
Migrate to Containers using the Migration Assessment Tool Earned 10월 23, 2024 EDT
BI Reporting: Looker Visualization on BigQuery Earned 10월 23, 2024 EDT
Migrating Hadoop Workloads Earned 10월 23, 2024 EDT
AWS EC2 to Compute Engine Earned 10월 23, 2024 EDT
On-Premises VMware to Compute Engine Earned 10월 23, 2024 EDT
Generative AI Fundamentals Earned 10월 23, 2024 EDT
Selling the Platform & Building Client Trust Earned 10월 23, 2024 EDT
Unlocking the Power of Google Cloud Generative AI for Partners Earned 10월 23, 2024 EDT
엔드 투 엔드 SDLC를 위한 Gemini Earned 10월 23, 2024 EDT
Technology + Beyond the UI Earned 10월 15, 2024 EDT
Innovating with Google Cloud Artificial Intelligence Earned 10월 15, 2024 EDT
Mandiant Fundamentals Earned 10월 15, 2024 EDT
Chronicle SIEM Fundamentals Earned 10월 15, 2024 EDT
Google Cloud Generative AI Trailblazer Earned 10월 14, 2024 EDT
Customer Engagement Suite with Google AI Architecture Earned 10월 14, 2024 EDT
Google Security Operations - SOAR Developer Earned 10월 14, 2024 EDT
Digital Transformation with Google Cloud Earned 10월 11, 2024 EDT
이미지 캡셔닝 모델 만들기 Earned 10월 10, 2024 EDT
인코더-디코더 아키텍처 Earned 10월 10, 2024 EDT
어텐션 메커니즘 Earned 10월 10, 2024 EDT
이미지 생성 소개 Earned 10월 10, 2024 EDT
Transformer 모델 및 BERT 모델 Earned 10월 10, 2024 EDT
Exploring Data Transformation with Google Cloud Earned 10월 9, 2024 EDT
Modernization of Applications using Openshift on Google Cloud Earned 10월 9, 2024 EDT
Migrating Pivotal Cloud Foundry (PCF) to Google Cloud Earned 10월 9, 2024 EDT
Azure Virtual Machines to Compute Engine Earned 10월 9, 2024 EDT
Migrating Oracle Workloads to Google Cloud Earned 10월 9, 2024 EDT
Networking in Google Cloud VMware Engine Earned 10월 9, 2024 EDT
Google Backup and Disaster Recovery Earned 10월 9, 2024 EDT
.NET Modernization Earned 10월 9, 2024 EDT
Google API products: A key to modern application development Earned 10월 9, 2024 EDT
Modernization of Java Applications for Google Cloud Earned 10월 9, 2024 EDT
Document AI: Building a Custom Document Extractor Earned 10월 9, 2024 EDT
Getting Started with Google Cloud VMware Engine Earned 10월 9, 2024 EDT
생성형 AI를 위한 머신러닝 작업(MLOps) Earned 10월 9, 2024 EDT
책임감 있는 AI: Google Cloud를 통한 AI 원칙 적용하기 Earned 9월 22, 2024 EDT
보안 엔지니어를 위한 Gemini Earned 8월 31, 2024 EDT
Google Sheets의 Gemini Earned 8월 31, 2024 EDT
Gmail의 Gemini Earned 8월 31, 2024 EDT
Google Workspace를 위한 Gemini 소개 Earned 8월 31, 2024 EDT
책임감 있는 AI 소개 Earned 8월 23, 2024 EDT
클라우드 설계자를 위한 Gemini Earned 8월 23, 2024 EDT
대규모 언어 모델 소개 Earned 8월 23, 2024 EDT
생성형 AI 소개 Earned 8월 23, 2024 EDT

Hands on course covering the main uses of extends and the three primary LookML objects extends are used on as well as some advanced usage of extends.

자세히 알아보기

This course educates partners on key concepts around deploying Google Cloud VMware Engine (GCVE) and leveraging HCX to migrate VMs from on-premises VMware to GCVE.

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In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.

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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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This course explores the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel. 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 will learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents. 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 on workspace transformation guides participants through modules designed to optimize and transform business environments using Google Workspace. It covers the Google Workspace Customer Success Methodology, provisioning processes, authentication and system access, mail routing, migration strategies, and coexistence planning to ensure a seamless transition and effective implementation.

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This course focuses on how you can leverage the Google Cloud Analytics and AI/ML offerings to integrate and innovate with SAP

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Google Workspace를 위한 Gemini는 사용자에게 생성형 AI 기능에 대한 액세스를 제공하는 부가기능입니다. 이 과정은 동영상 강의, 실습, 실제 사례를 사용하여 Google Drive의 Gemini가 제공하는 기능을 상세하게 살펴봅니다. 이 과정을 완료하면 Google Drive의 Gemini를 자신 있게 활용하여 워크플로를 개선할 수 있는 지식과 기술을 얻게 됩니다.

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Google Workspace를 위한 Gemini는 사용자에게 생성형 AI 기능에 대한 액세스를 제공하는 부가기능입니다. 이 과정에서는 Google Meet의 Gemini 기능에 대해 자세히 알아봅니다. 동영상 강의, 실습 활동, 실제 사례를 통해 Google Meet의 Gemini 기능을 종합적으로 이해할 수 있습니다. Gemini를 사용하여 배경 이미지를 생성하고, 동영상 품질을 개선하고, 자막을 번역하는 방법을 배웁니다. 본 과정을 마치면 Google Meet의 Gemini를 자신 있게 활용하여 화상 회의의 효과를 극대화하는 데 필요한 지식과 기술을 갖추게 됩니다.

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Google Workspace를 위한 Gemini는 고객에게 Google Workspace의 생성형 AI 기능을 제공하는 부가기능입니다. 이 미니 학습 과정에서는 Gemini의 주요 기능을 살펴보고 이러한 기능으로 Google Slides의 생산성과 효율성을 향상하는 방법을 알아봅니다.

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이 과정에서는 일부 Google Workspace 사용자에게 제공되는 온라인 동영상 제작 도구이자 편집 앱인 Google Vids에 대해 알아봅니다. 강의와 데모를 통해 동영상으로 강력한 스토리를 만들고 전달하는 방법을 학습합니다. 미디어, 오디오, 동영상 클립을 손쉽게 삽입하고, 스타일을 맞춤설정하며, 완성된 콘텐츠를 쉽게 공유하는 방법도 배웁니다. 일부 Google Vids 기능은 생성형 AI를 사용해 작업 효율성을 높여 줍니다. Gemini를 포함한 생성형 AI 도구는 부정확하거나 부적절한 정보를 제안할 수 있다는 점에 유의하세요. Gemini 기능을 의료, 법률, 금융 또는 기타 전문가의 조언으로 신뢰해서는 안 됩니다. 또한 Gemini 기능의 제안은 Google의 입장을 대변하지 않으며 Google이 작성한 것으로 간주해서는 안 된다는 점에 유의하세요.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Snowflake to BigQuery. Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners' understanding of the topics. "This learning path aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Snowflake to BigQuery.

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DORA (DevOps Research & Assessment) is a research program, an assessment tool, a report publisher, and more. Together, these products create a compelling customer story that defines the industry standard for successful DevOps and technology transformation, and provides personalized steps to accelerate the customer journey. DORA enables Googlers and Partners to bring DevOps research and practices to Google Cloud Customers. This course provides an introduction to DORA and a guide on how to successfully complete a DORA assessment for your customer. Engaging customers in DORA assessment provides invaluable insights into the customer’s organization, and helps you better support your customer. The DORA training was originally designed for and only made available to Google Teams, however we’ve recognized how beneficial it would be for our Partners and are now offering our Partners exclusive access to the DORA training and products, so they can benefit from DORA’s research and practices …

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This course is for deployment personnel of Google Cloud and its partner organizations who are tasked with managing cultural change and skill gaps of customers adopting Google Workspace, engaging sponsors and enlisting the support of customer stakeholders, communicating the anticipated changes to the customer and their users. It will guide you through the Workspace change management methodology and all phases of the customer journey.

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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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This is an introductory course to all solutions in the Conversational AI portfolio and the Gen AI features that are available to transform them. The course also explores the business case around Conversational AI, and the use cases and user personas addressed by the solution. 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.

자세히 알아보기

Google Workspace를 위한 Gemini는 사용자에게 생성형 AI 기능에 대한 액세스를 제공하는 부가기능입니다. 이 과정은 동영상 강의, 실습, 실제 사례를 사용하여 Google Docs의 Gemini가 제공하는 기능을 상세하게 살펴봅니다. 학습자는 Gemini를 사용하여 프롬프트를 바탕으로 텍스트 콘텐츠를 생성하는 방법을 확인하게 됩니다. 또한, 이미 작성한 텍스트를 Gemini로 수정하는 방법을 알아봅니다. 이러한 Gemini 활용을 통해 전체적인 생산성을 향상할 수 있습니다. 이 과정을 완료하면 Google Docs의 Gemini를 자신 있게 활용하여 텍스트 콘텐츠를 향상할 수 있는 지식과 기술을 얻게 됩니다.

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Want to learn more about Google Cloud? Grow your Google Cloud knowledge, strengthen your skills to win with customers, and scale your Google Cloud business. Find it here in one handy location.

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Learn the technical aspects you need to know about Chronicle and how it can help you detect and action threats.

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This course covers the basline skills needed for the Chronicle Security Operations Platform. The modules will cover specific actions and features that security engineers should become familiar with to start using the toolset.

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Google Threat Intelligence provides unmatched visibility into threats by delivering detailed and timely threat intelligence to security teams around the world. This course covers the various capabilities of Google Threat Intelligence and common ways that organizations use this product to proactively mitigate threats.

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This quiz tests your GDC Air-Gapped Security Operator Fundamental knowledge.

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This course gives you a deep dive into the workflows of Tier 1 and Tier 2 security analysts.

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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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이 과정은 머신러닝 실무자에게 생성형 AI 모델과 예측형 AI 모델을 평가하는 데 필요한 도구, 기술, 권장사항을 제공합니다. 모델 평가는 프로덕션 단계의 ML 시스템이 안정적이고 정확하고 성능이 우수한 결과를 제공할 수 있게 하는 중요한 분야입니다. 강의 참가자는 다양한 평가 측정항목, 방법, 각각 다른 모델 유형과 작업에 적합한 애플리케이션에 대해 깊이 있게 이해할 수 있습니다. 이 과정에서는 생성형 AI 모델의 고유한 문제를 강조하고 이를 효과적으로 해결하기 위한 전략을 소개합니다. 강의 참가자는 Google Cloud의 Vertex AI Platform을 활용해 모델 선택, 최적화, 지속적인 모니터링을 위한 견고한 평가 프로세스를 구현하는 방법을 알아볼 수 있습니다.

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This training aims to up-skill Google Cloud partners to deliver customer engagements through Delivery Navigator for available technical practice offerings. Learners will be able to navigate around the Delivery Navigator platform, select the desired method(s), and export the project WBS to a desired work management tool and Shared Google Drive. Sample artefacts are available through the Delivery Navigator methods and will be provided for reference. Contents of this course will be updated as new features are released for the Delivery Navigator platform.

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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.

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This course has been updated, please enroll in the new Elastic Google Cloud Infrastructure: Scaling and Automation.

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Imagen provides a suite of generative AI tools to help you accelerate your creative workflows. This course provides you with demonstrations of all the key features currently found in Imagen.

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This course gives you a deep dive into the workflows of Tier 3 analysts.

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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.

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This course will familiarize you with the core functionality of Chronicle, including the user interface, connections, and settings.

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The Cloud Foundations Customer Onboarding: Best Practices course enables partners to onboard customers on Google Cloud efficiently and in minimum time, by imparting knowledge, IP, and best practices from the Technical Onboarding Center (TOC) team at Global Delivery Center (GDC). The course explores Cloud Identity and organization, users and groups, administrative access, and resource hierarchy. It also examines network configuration, hybrid connectivity, logging and monitoring, and organizational security.

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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. 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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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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The Google Cloud Rapid Migration & Modernization Program (RaMP) is a holistic, end-to-end migration/modernization program that helps customers & partners leverage expertise and best practices, lower risk, control costs, and simplify a customer's path to cloud success. This course will give an overview of the program and some of the tools and best practices available to support customer migrations & modernizations.

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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology. 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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This workload aims to upskill Google Cloud partners to explore various VM migration types and their implications, including Backup and DR services, GCVE-Protected, and other backup, restore, and disaster recovery options available. They will explore when Backup and Restore can be used for VM migration. They will also identify common Disaster Recovery options and explore the use cases, capabilities, license levels, and components of VMware HCX. Additionally, learners will demonstrate installing, upgrading, and configuring VMware HCX and using HCX for live or bulk VM migrations.

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In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.

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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.

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This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.

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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.

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This course helps you understand how to use Chronicle to properly handle security incidents.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of Migration from Teradata to BigQuery using the Data Transfer Service and the Teradata TPT Export Utility. Sample Data will be used during both methods. Learners will complete a challenge lab that focuses on the process of transferring both schema, data and SQL from a Teradata data warehouse to BigQuery.

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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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This course enables system integrators and partners to understand the principles of automated migrations, plan legacy system migrations to Google Cloud leveraging G4 Platform, and execute a trial code conversion.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from PostgreSQL to CloudSQL using the Database Migration Service.

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This course provides comprehensive skills on VM migration, from the initial assessment through the final implementation through presentations, demonstrations, and whiteboard session.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from five products hosted on Cloudera or Hortonworks to corresponding Google Cloud services and hosted products. The migration solutions addressed will be: HDFS data to Google Cloud Dataproc and Cloud Storage Hive data to Cloud Dataproc and the Cloud Dataproc Metastore Hive data to Google Cloud BigQuery Impala data to Google Cloud BigQuery HBase to Google Cloud Bigtable Sample data will be used during all five migrations. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners understanding of the topics.

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This course aims to upskill Google Cloud partners to perform specific tasks of migrating data from Microsoft SQL Server to CloudSQL using the built-in replication capabilities of SQL Server. Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data, and related processes to corresponding Google Cloud products. One or more challenge labs will test the learner's understanding of the topics.

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Migration from MySQL to Cloud Spanner using Dataflow that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.

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Migration from MySQL to Cloud SQL using Database Migration Service that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from PostgreSQL to AlloyDB using the Database Migration Service. Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners understanding of the topics.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks for migrating data from AWS Redshift to BigQuery using BigQuery Data Transfer Service, which includes sample mock data. Learners will complete a challenge lab that focuses on the process of transferring both schema and data from a Redshift data warehouse to BigQuery.

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In this course, you explore the four components that make up the BigQuery Migration Service. They are Migration Assessment, SQL Translation, Data Transfer Service, and Data Validation. You will use each of these tools to perform a migration using to BigQuery.

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This course educates partners on key concepts of Google’s Migrate to Containers. It will cover planning, workload fitness for conversion, deployment with a processing cluster, and the migration process.

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This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating workloads from Hadoop environments to corresponding Google Cloud services and hosted products. The following will addressed will be: The Hadoop ecosystem and products Hadoop architecture and post migration architectures to Google Cloud Assessment Data transfer options Workload migrations, namely: Spark to Dataproc Serverless, Apache Oozie to Composer (Airflow), and Hive to BigQuery Security and governance Logging and Monitoring

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Migration from AWS EC2 to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.

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Migration from on-premises VMware to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.

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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities, learn to identify high-impact use cases, and develop the skills to demonstrate and integrate these technologies seamlessly into client solutions and operations.

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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities and learn to identify high-impact use cases.

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이 과정에서는 Google Cloud의 생성형 AI 기반 파트너인 Gemini가 Google 제품 및 서비스를 사용해 애플리케이션을 개발, 테스트, 배포, 관리하는 데 어떤 도움이 되는지 알아봅니다. Gemini의 도움을 받아 웹 애플리케이션을 개발 및 빌드하고, 애플리케이션의 오류를 수정하고, 테스트를 개발하고, 데이터를 쿼리하는 방법을 배웁니다. 실무형 실습을 통해 Gemini로 소프트웨어 개발 수명 주기(SDLC)가 얼마나 개선되는지 경험할 수 있습니다. Duet AI의 이름이 Google의 차세대 모델인 Gemini로 변경되었습니다.

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In this course you will discover additional tools for your toolbox for working with complex deployments, building robust solutions, and delivering even more value.

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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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Learn which Mandiant products directly enhance or augment capabilities provided by Chronicle SIEM and SOAR and how those products integrate into our workflow.

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This course will provide you with an overview of SIEM technology to set the stage for the differentiation and expansion of capabilities that Chronicle SIEM provides.

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This course is for Google Cloud’s top partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities and learn to identify high-impact use cases. Those who complete the training and assessment will receive the Google Cloud Generative AI Trailblazer badge through Skills Boost.

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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 was renamed to Conversational Insights.

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This course helps developers customize Chronicle and augment its abilities with third party integrations.

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There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.

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이 과정에서는 딥 러닝을 사용해 이미지 캡션 모델을 만드는 방법을 알아봅니다. 인코더 및 디코더와 모델 학습 및 평가 방법 등 이미지 캡션 모델의 다양한 구성요소에 대해 알아봅니다. 이 과정을 마치면 자체 이미지 캡션 모델을 만들고 이를 사용해 이미지의 설명을 생성할 수 있게 됩니다.

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이 과정은 기계 번역, 텍스트 요약, 질의 응답과 같은 시퀀스-투-시퀀스(Seq2Seq) 작업에 널리 사용되는 강력한 머신러닝 아키텍처인 인코더-디코더 아키텍처에 대한 개요를 제공합니다. 인코더-디코더 아키텍처의 기본 구성요소와 이러한 모델의 학습 및 서빙 방법에 대해 알아봅니다. 해당하는 실습 둘러보기에서는 TensorFlow에서 시를 짓는 인코더-디코더 아키텍처를 처음부터 간단하게 구현하는 코딩을 해봅니다.

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이 과정에서는 신경망이 입력 시퀀스의 특정 부분에 집중할 수 있도록 하는 강력한 기술인 주목 메커니즘을 소개합니다. 주목 메커니즘의 작동 방식과 이 메커니즘을 다양한 머신러닝 작업(기계 번역, 텍스트 요약, 질문 답변 등)의 성능을 개선하는 데 활용하는 방법을 알아봅니다.

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이 과정에서는 최근 이미지 생성 분야에서 가능성을 보여준 머신러닝 모델 제품군인 확산 모델을 소개합니다. 확산 모델은 열역학을 비롯한 물리학에서 착안했습니다. 지난 몇 년 동안 확산 모델은 연구계와 업계 모두에서 주목을 받았습니다. 확산 모델은 Google Cloud의 다양한 최신 이미지 생성 모델과 도구를 뒷받침합니다. 이 과정에서는 확산 모델의 이론과 Vertex AI에서 이 모델을 학습시키고 배포하는 방법을 소개합니다.

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이 과정은 Transformer 아키텍처와 BERT(Bidirectional Encoder Representations from Transformers) 모델을 소개합니다. 셀프 어텐션 메커니즘 같은 Transformer 아키텍처의 주요 구성요소와 이 아키텍처가 BERT 모델 빌드에 사용되는 방식에 관해 알아봅니다. 또한 텍스트 분류, 질문 답변, 자연어 추론과 같이 BERT를 활용할 수 있는 다양한 작업에 대해서도 알아봅니다. 이 과정은 완료하는 데 대략 45분이 소요됩니다.

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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences. “Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible. 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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This course focuses on modernizing applications using OpenShift on Google Cloud. Throughout this course, you'll gain the skills necessary to describe and understand OpenShift and successfully re-platform it to Google Cloud.

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Welcome to the course focusing on the Migration from Pivotal Cloud Foundry to Google Cloud. This program offers a practical demonstration that guides you through the step-by-step process of transitioning applications seamlessly between these two platforms. Throughout this course, you'll engage in hands-on exercises and demos, providing a proof-of-concept journey. This course provides insights into Pivotal Cloud Foundry and Tanzu Kubernetes Grid (TKG), and their roles in cloud infrastructure. It includes hands-on sessions for installing Tanzu CLI. You'll also learn to deploy management clusters efficiently, organize cloud resources, and create workload clusters. Additionally, you will perform a workload migration from Tanzu Kubernetes Grid to Google Kubernetes Engine (GKE) and containerize an applications on Google Cloud.

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Migration from Azure to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of rehosting Oracle Workloads on Google Cloud.

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This workload aims to upskill Google Cloud partners regarding various network configuration tasks related to VMware Engine and its integration with Google Cloud VPC, on-premises connectivity, DNS setup, service subnets, internet access, and overall network interoperability.

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This workload aims to upskill Google Cloud partners to deploy and manage Google Backup and Disaster Recovery (BDR). The following will be addressed: the core components and business value of Google BDR, the prerequisites before installing Google BDR, the initial deployment of Google BDR, creating and configuring components of a Backup Plan, the components of a Backup Plan, discovering VMware and Compute Engine VMs, and protecting, backing up, and restoring VMs.

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This learning path aims to upskill Google Cloud partners to perform the specific tasks associated with the priority workload. Learners will discover the specific tasks in rehosting applications from on-premises to Google Cloud. It also aims to re-platform applications to run in GKE. Learners will perform the tasks of Migrating MySQL, Angular, and .NET applications from their on-premises machines to Google Cloud VM instances. Sample code will be used during the migration. Learners will complete a challenge lab that focuses on the critical steps in a rehosting exercise - copying over code for the back-end, front-end, and middle-tier applications and validating that the applications have been migrated correctly. Learners will also complete a challenge lab that focuses on the critical steps in a re-platforming exercise - creating back-end, front-end, and middle-tier Docker images, deploying the same in the GKE cluster, and validating that the application has been deployed correctly.

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Outline the key steps in publishing an API to deliver selective company information to applications created by external developers.

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This course aims to upskill Google Cloud partners to perform specific tasks in rehosting applications from on-premise to Google Cloud. It also aims to re-platform applications to run in GKE. Learners will perform the tasks of Migrating MySQL, Angular, and Java applications from their on-premise machines to Google Cloud VM instances. Sample code will be used during the migration.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with building a Custom Doc Extractor using the Google Cloud AI solution. The following will be addressed: Service: Document AI Task: Extract fields Processors: Custom Document Extractor and Document Splitter Prediction: Using Endpoint to programmatically extract fields

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This workload aims to upskill Google Cloud Partners about what Google Cloud VMware Engine is, design considerations, and basic implementation. It will also cover interoperability with on-premises vSphere and real world use cases for deployment. Finally, it will cover how VMware Engine compares to other cloud providers' offerings of VMware as a Service and future plans for VMware Engine.

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이 과정에서는 생성형 AI 모델을 배포하고 관리할 때 MLOps팀이 직면하는 고유한 과제를 파악하는 데 필요한 지식과 도구를 제공하고 Vertex AI가 어떻게 AI팀이 MLOps 프로세스를 간소화하고 생성형 AI 프로젝트에서 성공을 거둘 수 있도록 지원하는지 살펴봅니다.

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기업에서 인공지능과 머신러닝의 사용이 계속 증가함에 따라 책임감 있는 빌드의 중요성도 커지고 있습니다. 대부분의 기업은 책임감 있는 AI를 실천하기가 말처럼 쉽지 않습니다. 조직에서 책임감 있는 AI를 운영하는 방법에 관심이 있다면 이 과정이 도움이 될 것입니다. 이 과정에서 책임감 있는 AI를 위해 현재 Google Cloud가 기울이고 있는 노력, 권장사항, Google Cloud가 얻은 교훈을 알아보면 책임감 있는 AI 접근 방식을 구축하기 위한 프레임워크를 수립할 수 있을 것입니다.

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이 과정에서는 Google Cloud의 생성형 AI 기반 파트너인 도구인 Gemini가 클라우드 환경 및 리소스 보호에 어떤 도움이 되는지 알아봅니다. Google Cloud의 환경에 예시 워크로드를 배포하고, Gemini를 이용해 잘못된 보안 구성을 확인 및 해결하는 방법을 배웁니다. 실무형 실습을 통해 Gemini가 클라우드 보안 상황을 어떻게 개선하는지 경험할 수 있습니다. Duet AI의 이름이 Google의 차세대 모델인 Gemini로 변경되었습니다.

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Google Workspace를 위한 Gemini는 고객이 Google Workspace에서 생성형 AI 기능을 사용할 수 있도록 하는 부가기능입니다. 이 미니 학습 과정에서는 Gemini의 주요 기능을 살펴보고 이러한 기능으로 Google Sheets의 생산성과 효율성을 향상하는 방법을 알아봅니다.

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Google Workspace를 위한 Gemini는 고객에게 Google Workspace의 생성형 AI 기능을 제공하는 부가기능입니다. 이 미니 학습 과정에서는 Gemini의 주요 기능을 살펴보고 이러한 기능으로 Gmail의 생산성과 효율성을 향상하는 방법을 알아봅니다.

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Google Workspace를 위한 Gemini는 고객에게 Google Workspace의 생성형 AI 기능을 제공하는 부가기능입니다. 이 학습 과정에서는 Gemini의 주요 기능을 살펴보고 이러한 기능으로 Google Workspace의 생산성과 효율성을 향상하는 방법을 알아봅니다.

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책임감 있는 AI란 무엇이고 이것이 왜 중요하며 Google에서는 어떻게 제품에 책임감 있는 AI를 구현하고 있는지 설명하는 입문용 마이크로 학습 과정입니다. Google의 7가지 AI 원칙도 소개합니다.

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이 과정에서는 Google Cloud의 생성형 AI 기반 도우미인 Gemini가 관리자의 인프라 프로비저닝을 어떻게 도와주는지 알아봅니다. 인프라에 관해 설명하고, GKE 클러스터를 배포하고, 기존 인프라를 업데이트하도록 Gemini에 프롬프트를 입력하는 방법을 배울 수 있습니다. 또한 실무형 실습을 통해 Gemini가 GKE 배포 워크플로를 어떻게 개선하는지 경험할 수 있습니다. Duet AI의 이름이 Google의 차세대 모델인 Gemini로 변경되었습니다.

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이 과정은 입문용 마이크로 학습 과정으로, 대규모 언어 모델(LLM)이란 무엇이고, LLM을 활용할 수 있는 사용 사례로는 어떤 것이 있으며, 프롬프트 조정을 사용해 LLM 성능을 개선하는 방법은 무엇인지 알아봅니다. 또한 자체 생성형 AI 앱을 개발하는 데 도움이 되는 Google 도구에 대해서도 다룹니다.

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생성형 AI란 무엇이고 어떻게 사용하며 전통적인 머신러닝 방법과는 어떻게 다른지 설명하는 입문용 마이크로 학습 과정입니다. 직접 생성형 AI 앱을 개발하는 데 도움이 되는 Google 도구에 대해서도 다룹니다.

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