Google Cloud
Data Engineering, Big Data, and Machine Learning on GCP Specialization

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Google Cloud

Data Engineering, Big Data, and Machine Learning on GCP Specialization

Data Engineering on Google Cloud. Launch your career in Data Engineering. Deliver business value with big data and machine learning.

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Get in-depth knowledge of a subject
4.6

(12,535 reviews)

Intermediate level
Some related experience required
4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.6

(12,535 reviews)

Intermediate level
Some related experience required
4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

Details to know

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Taught in English

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  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Google Cloud

Specialization - 4 course series

What you'll learn

  • Differentiate between data lakes and data warehouses.

  • Explore use-cases for each type of storage and the available data lake and warehouse solutions on Google Cloud.

  • Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.

  • Examine why data engineering should be done in a cloud environment.

Skills you'll gain

Category: Data Warehousing
Category: Google Cloud Platform
Category: Cloud Storage
Category: Data Lakes
Category: Data Analysis
Category: Data Storage
Category: Data Modeling
Category: Data Pipelines
Category: SQL
Category: Cloud Development
Category: Data Architecture
Category: Data Infrastructure

What you'll learn

  • Determine whether batch data pipelines are the correct choice for your business use case.

  • Design and build scalable batch data pipelines for high-volume ingestion and transformation.

  • Implement data quality controls within batch pipelines to ensure data integrity.

  • Orchestrate, manage, and monitor batch data pipeline workflows, implementing error handling and observability using logging and monitoring tools.

Skills you'll gain

Category: Apache Spark
Category: Data Transformation
Category: Google Cloud Platform
Category: Dataflow
Category: Data Pipelines
Category: Data Processing
Category: Data Integration
Category: Data Wrangling
Category: Big Data
Category: Apache Airflow
Category: Extract, Transform, Load
Category: Serverless Computing
Category: Apache Hadoop

What you'll learn

  • Ingest and manage streaming data using Pub/Sub and Managed Service for Apache Kafka

  • Build and deploy streaming data pipelines with Dataflow

  • Implement streaming data solutions for real-time analytics and application serving with BigQuery and Bigtable

Skills you'll gain

Category: Google Cloud Platform
Category: Performance Tuning
Category: Big Data
Category: Scalability
Category: Data Processing
Category: SQL
Category: Data Architecture
Category: Ad Hoc Analysis
Category: Real Time Data
Category: Data Pipelines
Category: Advanced Analytics

What you'll learn

  • Differentiate between ML, AI and deep learning.

  • Discuss the use of ML API’s on unstructured data.

  • Execute BigQuery commands from notebooks.

  • Create ML models by using SQL syntax in BigQuery and without coding using Vertex AI AutoML.

Skills you'll gain

Category: Google Cloud Platform
Category: Applied Machine Learning
Category: Machine Learning
Category: Unstructured Data
Category: Jupyter
Category: Artificial Intelligence
Category: Data Pipelines
Category: Tensorflow
Category: Big Data
Category: MLOps (Machine Learning Operations)

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Instructor

Google Cloud Training
Google Cloud
2,017 Courses3,752,489 learners

Offered by

Google Cloud

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