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Training courses are meant to help candidates to learn about the Google exam syllabus and prepare well. It has hands-on labs and expert support that will allow you to get in-depth knowledge of each domain covered in the test. So, these are some of the best training courses offered by Google for the Professional Data Engineer certification exam.

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The Google Professional Data Engineer certification is designed to equip the individuals with the required knowledge and skills to enable data-driven decision-making through collecting, transforming, and publishing data. To earn this certificate, the candidates will be required to pass a single test measuring their skills in leveraging, deploying, and continuously training pre-existing machine learning models. The qualifying exam also evaluates the ability of the applicants to design, build, operationalize, monitor, and secure data processing systems.

How to book Google Professional Data Engineer Exams

The registration for the Google Professional Data Engineer Exam follows the steps given below.

• Step2: Sign in or sign up to your Google Cloud Webassessor account
• Step4: Take the date of the exam, choose exam center and make further payment using payment method like credit/debit etc.
• Step3: Search for the exam name Google Professional Data Engineer
• Step1: Visit the Google Cloud Webassessor Website

Reference: https://cloud.google.com/certification/data-engineer

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Google Cloud Big Data & Machine Learning Fundamentals course

This course is a gateway to introduce you to Google Cloud's big data and different machine learning functions. However, to successfully pass this training, you have to attain one year of experience in SQL, extract transform, data modeling, machine learning, programming in Python, and load activities. So, the objectives of the course are the following:

• Recognize the purpose of the key Big data and Machine Learning products in Google Cloud
• Create ML models using BigQuery ML, APIs, and AutoML.
• Hire BigQuery and Cloud SQL for interactive data analysis
• Utilize Cloud SQL & Dataproc to migrate existing MySQL, Pig, Spark, or Hive workloads to Google Cloud