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Data Engineering with Google Cloud 전문 자격증
Advance your career in data engineering
제공자:
Data Engineering with Google Cloud 전문 자격증Google 클라우드배울 내용
Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.
Employ BigQuery to carry out interactive data analysis.
Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.
Choose between different data processing products on Google Cloud.
귀하가 습득할 기술
이 전문 자격증 정보
87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification.
Here's what you have to do
1) Complete the Coursera Data Engineering Professional Certificate
2) Review other recommended resources for the Google Cloud Professional Data Engineer certification exam
3) Review the Professional Data Engineer exam guide
4) Complete Professional Data Engineer sample questions
5) Register for the Google Cloud certification exam (remotely or at a test center)
Applied Learning Project
This professional certificate incorporates hands-on labs using Qwiklabs platform.These hands on components will let you apply the skills you learn. Projects incorporate Google Cloud Platform products used within Qwiklabs. You will gain practical hands-on experience with the concepts explained throughout the modules.
응용 학습 프로젝트
This Professional Certificate incorporates hands-on labs using our Qwiklabs platform.
These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google BigQuery, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.
학습자 경력 결과
41%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
20%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
완료하는 데 약 4개월이 걸립니다
권장 학습 속도: 주 4시간
영어
자막: 영어, 프랑스어, 포르투갈어 (유럽), 러시아어, 스페인어
학습자 경력 결과
41%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
20%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
완료하는 데 약 4개월이 걸립니다
권장 학습 속도: 주 4시간
영어
자막: 영어, 프랑스어, 포르투갈어 (유럽), 러시아어, 스페인어
이 전문 자격증에는 6개의 강좌가 있습니다.
Google Cloud Platform Big Data and Machine Learning Fundamentals
12,818개의 평가
This course introduces participants to the big data capabilities of Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud.
Modernizing Data Lakes and Data Warehouses with GCP
2,009개의 평가
The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud Platform in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.
Building Batch Data Pipelines on GCP
1,207개의 평가
Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud Platform for data transformation including BigQuery, executing Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Cloud Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud Platform using Qwiklabs.
Building Resilient Streaming Analytics Systems on GCP
942개의 평가
*Note: this is a new course with updated content from what you may have seen in the previous version of this Specialization.
제공자:
Google 클라우드
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
자주 묻는 질문
전문 분야를 완료하면 대학 학점을 받을 수 있나요?
Can I just enroll in a single course?
하나의 강좌에만 등록할 수 있나요?
이 강좌는 100% 온라인으로 진행되나요? 직접 참석해야 하는 수업이 있나요?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
