학습자들은 이 과정이 MLOps의 핵심 개념과 Vertex AI Feature Store의 실제 적용 방법을 배우는 데 매우 유익하다고 말합니다. 특히 핸즈온 실습과 스트리밍 수집 기능 구현을 통해 실무에 바로 적용 가능한 지식을 얻을 수 있었다는 평가가 많습니다. 강사님의 명확하고 간결한 설명 덕분에 이해하기 쉬웠다는 의견도 다수입니다. 다만, 고급 주제에 대한 심도 있는 내용이나 대규모 서비스 적용 예시는 다소 부족하며, GCP나 Vertex AI에 대한 사전 지식이 없는 경우 초기 설정에 시간이 소요될 수 있다고 언급됩니다. 전반적으로 MLOps 초급자 및 Vertex AI Feature Store 입문자에게 강력히 추천하는 과정입니다.

GCP 또는 Vertex AI에 대한 기초 지식이 있으면 학습에 더 유리합니다.

"실습 환경 설정에 다소 시간이 걸렸습니다. 처음 GCP를 사용하는 학습자에게는 초반 진입 장벽이 있을 수 있습니다."

"Vertex AI에 대한 사전 지식이 없으면 따라가기 좀 어려울 수도 있습니다."

"약간의 GCP 경험이 있으면 더 좋습니다."

복잡한 MLOps 및 Feature Store 개념을 쉽고 간결하게 전달합니다.

"MLOps 개념과 Vertex AI의 연동을 잘 설명해주는 과정입니다."

"복잡한 내용을 쉽고 간결하게 설명해 주어 좋았습니다."

"설명이 명확하고 따라하기 쉬웠습니다. 처음 접하는 사람에게도 좋은 출발점이 될 것 같아요."

최신 MLOps 트렌드를 다루며 실무에 바로 적용 가능한 지식을 제공합니다.

"최신 기술인 Feature Store를 다루는 점이 인상 깊었습니다. 실무에 바로 적용할 수 있는 내용이 많네요."

"실무에 바로 적용할 수 있는 지식을 얻을 수 있었고, MLOps 엔지니어에게 필수적인 내용이라고 생각합니다."

"최신 트렌드인 MLOps와 Feature Store를 Google Cloud 환경에서 배울 수 있어 좋았습니다."

Vertex AI Feature Store의 실질적인 활용법을 익히는 데 큰 도움이 됩니다.

"Vertex AI Feature Store를 실제로 사용해 볼 수 있어서 매우 유익했습니다. MLOps 파이프라인에 피처 스토어가 어떻게 통합되는지 실습을 통해 확실히 이해할 수 있었습니다."

"Google Cloud의 최신 MLOps 기능을 학습하는 데 최적화된 과정입니다... 특히 핸즈온 랩이 실제 환경과 유사하여 큰 도움이 되었습니다."

"실습 위주로 구성된 점이 가장 큰 장점입니다."

"실무에 바로 적용할 수 있는 지식을 얻을 수 있었고, MLOps 엔지니어에게 필수적인 내용이라고 생각합니다."

특정 기능에 집중하며, 고급 활용이나 MLOps 전반의 심화 내용은 부족합니다.

"일부 고급 주제는 좀 더 심도 깊은 설명이 있었으면 합니다."

"MLOps 전반에 대한 심화 내용은 기대하기 어렵습니다. 너무 Vertex AI Feature Store에만 국한된 느낌입니다."

"너무 기본적인 내용 위주였습니다. Vertex AI를 이미 사용해본 경험이 있는 사람에게는 새롭거나 깊이 있는 정보가 많지 않을 수 있습니다."

"이 과정은 Vertex AI의 특정 기능에 집중되어 있어 MLOps 전체 그림을 보고 싶은 분들에게는 아쉬울 수 있습니다."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in MLOps with Vertex AI: Manage Features - 한국어 with these activities:

教材の整理と復習

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コースの教材を整理し、重要な概念にフラグを立てて、復習できるようにします。

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追加のオンラインチュートリアルを完了する

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コースの内容を補完し、理解を深めるためのオンラインチュートリアルを見つけて完了します。

Browse courses on Vertex AI Feature Store

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Vertex AI Feature Store に関する追加資料を見つける
MLOps の実践に関するチュートリアルを見つける
見つけたリソースを完了する

ハンズオン演習を完了する

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コースで学んだ概念を強化するために、ハンズオン演習を完了します。

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Vertex AI Feature Store を使用してストリーミング収集を設定する

Four other activities

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Vertex AI Feature Store の使用に関するブログ記事を書く

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コースで学んだ内容を他の人と共有し、理解を深めるために、Vertex AI Feature Store の使用に関するブログ記事を書きます。

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ブログ記事のテーマを選択する
ブログ記事の構造を計画する
ブログ記事を執筆する
ブログ記事を編集し、校正する
ブログ記事を公開する

コースの概念を他の学生に説明する

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コースで学んだ概念を他の学生に説明することで、理解を深め、教えるスキルを向上させます。

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説明する概念を選択する
説明を計画する
説明を行う
フィードバックを受け取る

Vertex AI Feature Store に関するワークショップに参加する

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Vertex AI Feature Store に関する実践的な知識とスキルを深めるために、ワークショップに参加します。

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ワークショップを探す
ワークショップに申し込む
ワークショップに参加する

Vertex AI Feature Store の経験を持つメンターを探す

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Vertex AI Feature Store に関する理解を深めるために、経験豊富なメンターを見つけて相談します。

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メンターを探して連絡を取る

Career center

Learners who complete MLOps with Vertex AI: Manage Features - 한국어 will develop knowledge and skills that may be useful to these careers:

ML Engineer

ML Engineers design, develop, and deploy ML models. They work with data scientists, engineers, and other team members to ensure that ML models are accurate, reliable, and scalable. This course may be useful for ML Engineers who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Data Scientist

Data Scientists use data to solve business problems. They work with data engineers, ML engineers, and other team members to collect, analyze, and interpret data. This course may be useful for Data Scientists who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

See salaries and explore the career path for Data Scientist

Data Engineer

Data Engineers design, build, and maintain data pipelines that collect, process, and store data. They work with data scientists, analysts, and other team members to ensure that data is available in a timely and reliable manner. This course may be useful for Data Engineers who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Technical Program Manager

Technical Program Managers help plan, lead, and oversee the execution of technical projects. They work with engineers, stakeholders, and other team members to ensure that projects are completed on time, within budget, and to the required specifications. This course may be useful for Technical Program Managers who want to learn more about how to use MLOps tools and techniques to manage features in production ML systems.

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Data Architect

Data Architects design and implement data architectures. They work with other team members to ensure that data architectures are scalable, reliable, and secure. This course may be useful for Data Architects who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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DevOps Engineer

DevOps Engineers design, implement, and maintain software development and deployment processes. They work with other team members to ensure that software development and deployment processes are efficient and effective. This course may be useful for DevOps Engineers who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Solutions Architect

Solutions Architects design and implement solutions to meet the needs of customers. They work with other team members to ensure that solutions are effective and efficient. This course may be useful for Solutions Architects who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Software Engineer

Software Engineers design, develop, and maintain software systems. They work with other team members to ensure that software systems are reliable, scalable, and meet the needs of users. This course may be useful for Software Engineers who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Cloud Architect

Cloud Architects design, implement, and maintain cloud computing systems. They work with other team members to ensure that cloud computing systems are reliable, scalable, and meet the needs of users. This course may be useful for Cloud Architects who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Product Manager

Product Managers plan and manage the development of products. They work with other team members to ensure that products meet the needs of users. This course may be useful for Product Managers who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Technical Writer

Technical Writers create and maintain technical documentation. They work with other team members to ensure that technical documentation is accurate, clear, and concise. This course may be useful for Technical Writers who want to learn more about how to write documentation for Vertex AI Feature Store.

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DBA

DBAs design, implement, and maintain database systems. They work with other team members to ensure that database systems are reliable, scalable, and meet the needs of users. This course may be useful for DBAs who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Business Analyst

Business Analysts analyze business needs and develop solutions to meet those needs. They work with other team members to ensure that business solutions are effective and efficient. This course may be useful for Business Analysts who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Systems Engineer

Systems Engineers design, implement, and maintain computer systems. They work with other team members to ensure that computer systems are reliable, scalable, and meet the needs of users. This course may be useful for Systems Engineers who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Network Engineer

Network Engineers design, implement, and maintain computer networks. They work with other team members to ensure that computer networks are reliable, scalable, and meet the needs of users. This course may be useful for Network Engineers who want to learn more about how to use Vertex AI Feature Store to manage features in production ML systems.

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Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in MLOps with Vertex AI: Manage Features - 한국어.