Google Cloud Big Data and Machine Learning Fundamentals 한국어

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이 과정에서는 데이터-AI 수명 주기를 지원하는 Google Cloud 빅데이터 및 머신러닝 제품과 서비스를 소개합니다. Google Cloud에서 Vertex AI를 사용하여 빅데이터 파이프라인 및 머신러닝 모델을 빌드하는 프로세스, 문제점 및 이점을 살펴봅니다.

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What's inside

Syllabus

과정 소개

이 섹션에서는 빅데이터 및 머신러닝 기초 과정을 시작하는 학습자를 환영하고 과정 구조와 목표를 살펴봅니다.

Google Cloud의 빅데이터 및 머신러닝

이 섹션에서는 Google Cloud 인프라의 주요 구성요소를 살펴봅니다. Google Cloud의 데이터-AI 수명 주기를 지원하는 빅데이터 및 머신러닝 제품과 서비스도 소개합니다.

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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 Google Cloud Big Data and Machine Learning Fundamentals 한국어 with these activities:

구글 클라우드 플랫폼 이해하기

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Google Cloud Platform의 기본 사항을 검토하여 이 과정에 더욱 쉽게 참여할 수 있습니다.

Browse courses on Google Cloud Platform

Show steps

Google Cloud Platform 공식 문서 읽기
Google Cloud 플랫폼 튜토리얼 시청하기

빅데이터 파이프라인 구축 시나리오 설명하기

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실제 빅데이터 파이프라인 구축 시나리오를 설명하면 파이프라인 빌드와 관리에 대한 이해를 심화시킬 수 있습니다.

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업계 사례 연구 또는 케이스 스터디 조사하기
자체 시나리오 만들기
Google Cloud 워크샵 또는 웹 세미나 참석하기

Vertex AI AutoML 모델 최적화 문제 해결하기

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Vertex AI AutoML 모델 최적화 문제를 해결하면 모델 성능을 향상시키는 데 도움이 될 수 있습니다.

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Google Cloud Platform 문서에서 AutoML 최적화 기술 연구하기
Vertex AI AutoML 랩 또는 튜토리얼 연습하기
개인 프로젝트에서 AutoML 모델 최적화 테스트하기

Three other activities

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고급 머신러닝 모델 구축을 위한 팁 공유하기

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다른 학생과의 대화를 통해 고급 머신러닝 모델 구축에 대한 새로운 관점과 기술을 배우실 수 있습니다.

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연습 문제 및 과제 공동 작업하기
Google Cloud Platform 커뮤니티 포럼에서 토론하기
지역 미팅이나 해커톤 참석하기

빅데이터 분석 플랫폼을 위한 구조 설계하기

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빅데이터 분석 플랫폼 구조를 설계하면 이 과정에서 배우는 기술과 지식의 통합을 강화할 수 있습니다.

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데이터 조사 및 분석 수행하기
Google Cloud 솔루션 아키텍트와 협력하기
구조 설계 문서 작성하기

데이터-AI 라이브러리 및 도구에 기여하기

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데이터-AI 라이브러리 및 도구에 기여하면 이 과정에서 배우는 기술을 강화하고 커뮤니티에 환원할 수 있습니다.

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Google Cloud Platform 리포지토리 탐색하기
버그 보고하기 또는 기능 요청하기
코드 개선 또는 새로운 기능 구현하기

Career center

Learners who complete Google Cloud Big Data and Machine Learning Fundamentals 한국어 will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models. This course provides an overview of Google Cloud's machine learning platform, Vertex AI, and introduces the key concepts and techniques used in machine learning. By gaining practical experience in building and deploying machine learning models, you'll be well-prepared for a career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data. This course can serve as an introduction to Google Cloud's suite of big data and machine learning tools, which are commonly used by Data Scientists. With hands-on experience in using these tools, you'll be able to contribute to data science projects and pursue a career in this field.

See salaries and explore the career path for Data Scientist

Data Engineer

A Data Engineer designs, builds, and maintains data pipelines and infrastructure. This course provides an overview of Google Cloud's big data and machine learning tools, and introduces the key concepts and techniques used in data engineering. By gaining practical experience in working with these tools, you'll be well-prepared for a career as a Data Engineer.

See salaries and explore the career path for Data Engineer

Data Architect

A Data Architect designs, builds, and maintains data systems and infrastructure. This course provides an understanding of the Google Cloud data ecosystem and the principles of data engineering. By gaining hands-on experience in working with big data and machine learning tools, you'll be well-prepared to design and manage data systems as a Data Architect.

See salaries and explore the career path for Data Architect

Business Intelligence Analyst

A Business Intelligence Analyst analyzes data to identify trends and patterns that can help businesses make better decisions. This course provides an introduction to data engineering, big data, and machine learning, which are all essential skills for Business Intelligence Analysts. By gaining a strong understanding of how to work with data, you'll be able to contribute to business intelligence projects and pursue a career in this field.

See salaries and explore the career path for Business Intelligence Analyst

Data Analyst

A Data Analyst gathers, interprets, and presents complex data for business decision-making. This course helps build a foundation in data engineering and the machine learning lifecycle, which are essential skills in data analysis. By gaining a strong understanding of how to work with big data and machine learning, you'll be well-prepared for a career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Software Engineer

A Software Engineer designs, develops, and maintains software applications. This course provides an introduction to Google Cloud's big data and machine learning tools, which are increasingly used in software development. By gaining hands-on experience in working with these tools, you'll be able to build and deploy software applications that leverage big data and machine learning, and pursue a career as a Software Engineer.

See salaries and explore the career path for Software Engineer

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 Google Cloud Big Data and Machine Learning Fundamentals 한국어.

Pattern Recognition and Machine Learning

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패턴 인식과 머신러닝을 위한 통계적 및 수학적 기반에 대한 전반적인 개요를 제공합니다. 이 과정에서 머신러닝 모델 개발에 대한 추가 이론적 지식을 제공할 수 있습니다.

(English) Pattern Recognition and Machine Learning...

Hardcover

$$$

(English) Pattern Recognition and Machine Learning...

Paperback

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(English) Pattern Recognition and Machine Learning (text...

Unknown Binding

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