Vertex AI를 시작하기 위해 이 페이지에서는 Google Cloud 프로젝트를 만들고 Vertex AI API를 사용 설정하는 방법을 안내합니다. 이러한 작업을 수행할 권한이 없는 경우 관리자에게 프로젝트를 설정하고 Vertex AI를 사용 설정해 달라고 요청합니다. 또한 이 페이지에서는 로컬 개발 환경에서 Google Cloud CLI를 설정하는 방법도 설명합니다.
프로젝트 설정
프로젝트를 설정하려면 다음 단계를 따르세요.
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
이 섹션에서는 관리자가 Vertex AI를 사용하는 데 필요한 역할을 부여하는 방법을 설명합니다.
프로젝트를 식별할 수 있는 의미 있는 프로젝트 이름과 프로젝트 ID를 결정합니다.
조직에 속해 있거나 여러 프로젝트를 만들려는 경우 어떤 이름 지정 규칙과 폴더 계층 구조를 따르거나 따를 수 있는지 고려하여 프로젝트 구성을 명확히 하세요.
필요한 역할:
대부분의 Vertex AI 기능에 대한 액세스 권한은 Vertex AI 사용자(roles/aiplatform.user) IAM 역할이 부여하며, 대부분의 Vertex AI 사용자에게 충분합니다. Vertex AI 리소스를 완전히 제어하려면 Vertex AI 관리자(roles/aiplatform.admin) 역할을 요청할 수 있습니다.
이러한 역할과 다른 Vertex AI 역할 간의 차이점을 살펴보려면 IAM으로 Vertex AI 액세스 제어를 참조하세요.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-10(UTC)"],[],[],null,["# Set up a project and a development environment\n\nTo get you started using Vertex AI, this page guides you through how to\ncreate a Google Cloud project and enable the Vertex AI APIs. If you\ndon't have the permissions to perform these tasks,\n[ask an administrator](#ask_admin) to setup\na project and enable Vertex AI for you. Also covered in this page is\nhow to set up the Google Cloud CLI in your local development environment.\n\nSet up a project\n----------------\n\nFollow these steps to set up a project:\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Vertex AI API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Vertex AI API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n\n| **Note:** If you're an administrator setting up a project for a team, see [Set up a project for a team](/vertex-ai/docs/general/set-up-project).\n\nSet up authentication\n---------------------\n\n1. Select the tab for how you plan to use the samples on this page: \n\n### Console\n\n\nWhen you use the Google Cloud console to access Google Cloud services and\nAPIs, you don't need to set up authentication.\n\n### gcloud\n\nIn the Google Cloud console, activate Cloud Shell.\n\n[Activate Cloud Shell](https://console.cloud.google.com/?cloudshell=true)\n\n\nAt the bottom of the Google Cloud console, a\n[Cloud Shell](/shell/docs/how-cloud-shell-works)\nsession starts and displays a command-line prompt. Cloud Shell is a shell environment\nwith the Google Cloud CLI\nalready installed and with values already set for\nyour current project. It can take a few seconds for the session to initialize.\n\n### Python\n\n\nTo use the Python samples on this page in a local\ndevelopment environment, install and initialize the gcloud CLI, and\nthen set up Application Default Credentials with your user credentials.\n\n1.\n [Install](/sdk/docs/install) the Google Cloud CLI.\n\n2. If you're using an external identity provider (IdP), you must first\n [sign in to the gcloud CLI with your federated identity](/iam/docs/workforce-log-in-gcloud).\n\n3.\n After initializing the gcloud CLI, update it and install the required components:\n\n ```bash\n gcloud components update\n gcloud components install beta\n ```\n4. If you're using a local shell, then create local authentication credentials for your user account: \n\n```bash\ngcloud auth application-default login\n```\n5. You don't need to do this if you're using Cloud Shell.\n6. If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have [signed in to the gcloud CLI with your federated identity](/iam/docs/workforce-log-in-gcloud).\n\n\nFor more information, see\n[Set up ADC for a local development environment](/docs/authentication/set-up-adc-local-dev-environment)\nin the Google Cloud authentication documentation.\n\n### REST\n\n\nTo use the REST API samples on this page in a local development environment, you use the\ncredentials you provide to the gcloud CLI.\n\n1.\n [Install](/sdk/docs/install) the Google Cloud CLI.\n\n2. If you're using an external identity provider (IdP), you must first\n [sign in to the gcloud CLI with your federated identity](/iam/docs/workforce-log-in-gcloud).\n\n3.\n After initializing the gcloud CLI, update it and install the required components:\n\n ```bash\n gcloud components update\n gcloud components install beta\n ```\n\n\nFor more information, see\n[Authenticate for using REST](/docs/authentication/rest)\nin the Google Cloud authentication documentation.\n\n\u003cbr /\u003e\n\nAsk an administrator to set up a Vertex AI project for you\n----------------------------------------------------------\n\nThis section describes how an administrator grants the roles needed to use\nVertex AI.\n\n1. Determine a meaningful project name and project ID to identify your project. If you are part of an organization or plan to create multiple projects, consider what naming conventions and [folder](/resource-manager/docs/cloud-platform-resource-hierarchy#folders) hierarchies are followed, or could be followed, to make project organization clear.\n2. Required roles:\n 1. Access to most Vertex AI capabilities is granted by the [Vertex AI\n User](/vertex-ai/docs/general/access-control#aiplatform.user) `(roles/aiplatform.user)` IAM role and should suffice for most Vertex AI users. For full control of Vertex AI resources, you can request the [Vertex AI\n Administrator](/vertex-ai/docs/general/access-control#aiplatform.admin) `(roles/aiplatform.admin)` role. To explore the differences between these and other Vertex AI roles, see [Vertex AI access control\n with IAM](/vertex-ai/docs/general/access-control).\n 2. If you also intend to use [Vertex AI Workbench\n instances](/vertex-ai/docs/workbench/introduction) in Google Cloud, ask your administrator to grant you the [Notebooks\n Administrator](/iam/docs/understanding-roles#notebooks.admin) `(roles/notebooks.admin)` IAM role for the project, as well as the [Service\n Account User](/iam/docs/understanding-roles#iam.serviceAccountUser) `(roles/iam.serviceAccountUser)` IAM role on either the project or the [Compute Engine\n default service account](/compute/docs/access/service-accounts#default_service_account).\n 3. Additionally, to enable the necessary APIs, you either need the [Service\n Usage Admin](/iam/docs/understanding-roles#serviceusage.serviceUsageAdmin) `(roles/serviceusage.serviceUsageAdmin)` IAM role or your administrator needs to enable the APIs for you by following the first few steps.\n3. Ask your administrator to enable Vertex AI APIs for you. If you're granted the [Service\n Usage Admin](/iam/docs/understanding-roles#serviceusage.serviceUsageAdmin) `(roles/serviceusage.serviceUsageAdmin)` IAM role, then you'll be able to do this on your own.\n\n| **Note:** Certain tasks in Vertex AI require that you use additional Google Cloud products besides Vertex AI. For example, in most cases, you must use Cloud Storage and Artifact Registry when you create a custom training pipeline. You might need to perform additional setup tasks to use other Google Cloud products.\n\nWhat's next\n-----------\n\n- Read an [overview of\n Vertex AI](/vertex-ai/docs/start/introduction-unified-platform).\n\n- Walk through one of the [tutorials for using\n Vertex AI](/vertex-ai/docs/tutorials).\n\n- Learn how to\n [use the Vertex AI SDK for Python](/vertex-ai/docs/python-sdk/use-vertex-ai-python-sdk),\n which provides another way to interact with Vertex AI."]]
