Online Course – Certified Professional Internship in Data Engineering, Big Data, and Machine Learning on Google Cloud

Start a career in Data Engineering at Google Cloud. Deliver business value with big data and machine learning.

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קורס אונליין - התמחות מקצועית מוסמכת בהנדסת נתונים

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Confidence in cloud skills
  • Google Cloud Professional Data Engineer Exam Preparation
  • Deep understanding of data engineering
  • Hands-on experience with the Qwiklabs platform
  • Applying practical skills in projects
  • Working with BigQuery
  • Preparation with recommended resources
  • Understanding the Professional Data Engineering Exam Guide
  • Solving sample questions for professional data engineering

What you will learn in the course

Courses for which the course is suitable

  • Data Engineer
  • Data Analyst
  • Data key
  • Data Manager
  • Artificial Intelligence Expert
  • Information Systems Engineer
  • Cloud Solutions Developer
  • Technology Project Manager
  • Data Technology Consultant

Internship – 5-part course series

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 Google Cloud Professional Data Engineer exam, an industry-recognized certification.

Here’s what you need to do:

  • Complete the Data Engineering Professional Certificate on Coursera.
  • See additional recommended resources for Google Cloud Professional Data Engineer certification.
  • Review the Professional Data Engineering Exam Guide.
  • Complete the sample questions for professional data engineering.
  • Register for the Google Cloud Certification exam (remotely or at a testing center).

Hands-on Learning Project

This professional certificate includes hands-on labs using the Qwiklabs platform. These hands-on components will allow you to apply the skills you learned in the video lectures. Projects will include topics such as BigQuery, which is used and configured in Qwiklabs. You can expect to gain hands-on experience with the terms explained in the various modules.

Details of the courses that make up the specialization

Big Data and Machine Learning Fundamentals in Google Cloud

Course 1

Duration: 9 hours

Rating: 4.7 (16,088 ratings)

What will you learn?

  • Identify the data lifecycle to artificial intelligence.
  • Design streaming pipelines using Dataflow and Pub/Sub.
  • You’ve noticed different options for building machine learning solutions on Google Cloud.
  • Describe a machine learning workflow with Vertex AI.

Skills you will gain

  • Tensorflow
  • Bigquery
  • Google Cloud Platform
  • Cloud computing

Preventing data sinks and data warehouses with Google Cloud

Course 2

Duration: 8 hours

Rating: 4.7 (2,814 ratings)

What will you learn?

  • Distinguish between data pools and data warehouses.
  • To explore use cases for all types of storage.
  • Discuss the role of a data engineer.
  • Examine why data engineering should be performed in a cloud environment.

Building data pipelines in the process from a data screen in Google Cloud

Course 3

Duration: 17 hours

Rating: 4.5 (1,687 ratings)

What will you learn?

  • Overview of different data loading methods: EL, ELT, and ETL.
  • You ran Hadoop on Dataproc.
  • Build your data processing pipelines using Dataflow.
  • Manage data pipelines with Data Fusion and Cloud Composer.

Building resilient streaming analytics systems on Google Cloud

Course 4

Duration: 7 hours

Rating: 4.6 (1,245 ratings)

What will you learn?

  • Interpret use cases for real-time streaming analytics.
  • Manage data events using Pub/Sub.
  • Write streaming pipes and run transformations.
  • Use Dataflow, BigQuery, and Pub/Sub for real-time analysis and streaming.

Smart analytics, machine learning, and artificial intelligence on Google Cloud

Course 5

Duration: 6 hours

Rating: 4.6 (1,220 ratings)

What will you learn?

  • Distinguish between machine learning, artificial intelligence, and deep learning.
  • Discuss using machine learning APIs on unstructured data.
  • Run BigQuery commands from notebooks.
  • Create machine learning models using SQL in BigQuery.

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