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

Taught in English

60,368 already enrolled

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.6

(12,366 reviews)

Intermediate level
Some related experience required
1 month at 10 hours a week
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Specialization - 5 course series

Get in-depth knowledge of a subject

4.6

(12,366 reviews)

Intermediate level
Some related experience required
1 month at 10 hours a week
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Advance your subject-matter expertise

  • 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
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Specialization - 5 course series

Google Cloud Big Data and Machine Learning Fundamentals

Course 10 minutes4.7 (15,994 ratings)

What you'll learn

  • Identify the data-to-AI lifecycle on Google Cloud and the major products of big data and machine learning.

  • Design streaming pipelines with Dataflow and Pub/Sub and dDesign streaming pipelines with Dataflow and Pub/Sub.

  • Identify different options to build machine learning solutions on Google Cloud.

  • Describe a machine learning workflow and the key steps with Vertex AI and build a machine learning pipeline using AutoML.

Skills you'll gain

Category: Tensorflow
Category: Bigquery
Category: Google Cloud Platform
Category: Cloud Computing

Modernizing Data Lakes and Data Warehouses with Google Cloud

Course 28 hours4.7 (2,790 ratings)

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.

Building Batch Data Pipelines on Google Cloud

Course 317 hours4.5 (1,675 ratings)

What you'll learn

  • Review different methods of data loading: EL, ELT and ETL and when to use what

  • Run Hadoop on Dataproc, leverage Cloud Storage, and optimize Dataproc jobs

  • Build your data processing pipelines using Dataflow

  • Manage data pipelines with Data Fusion and Cloud Composer

What you'll learn

  • Interpret use-cases for real-time streaming analytics.

  • Manage data events using the Pub/Sub asynchronous messaging service.

  • Write streaming pipelines and run transformations where necessary.

  • Interoperate Dataflow, BigQuery and Pub/Sub for real-time streaming and analysis

Smart Analytics, Machine Learning, and AI on Google Cloud

Course 56 hours4.6 (1,208 ratings)

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.

Instructor

Google Cloud Training
Google Cloud
1,449 Courses2,598,885 learners

Offered by

Google Cloud

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