Data Engineering on Google Cloud course

It is a 4-day course that gives hands-on experience to the candidates and allows them to build data processing systems on Google Cloud. It will also show you how to design data processing systems, analyze data and build end-to-end data pipelines and machine learning. In order to get a better understanding of the course, you need to complete the big data machine learning course or get equivalent experience. This course also aids you in developing applications using a programming language such as Python and covers the following objective:

• Designing and building data processing systems on the Google Cloud Platform
• Influencing unstructured data using ML APIs on Cloud Dataproc
• Enable insights from streaming data
• Predicting machine models using TensorFlow and Cloud ML
• Processing batch and streaming data by using autoscaling data pipelines on Cloud Dataflow

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This course will show you how to manage big data including loading, extracting, cleaning, and validating data. At the end of the training, you can easily create machine learning and statistical models as well as visualizing query results. This program is a bit lengthy but you have to practice well to get the knowledge needed on the actual exam. These are the following modules covered in the course:

• Custom Model building Utilizing Cloud AutoML
• Serverless Data Processing with Cloud Dataflow
• Performing Spark on Cloud Dataproc
• Introduction to Building Batch Data Pipelines
• Serverless Messaging Using Cloud Sub/Pub
• Prebuilt ML Models APIs for Unsaturated Data
• Building a Data Warehouse
• Handling Data Pipelines with Cloud Composer and Cloud Data Fusion
• Big Data Analytics with Cloud Al Platform Notebook
• Bigtable Streaming Features and High-Throughput BigQuery
• Custom Model building Using SQL in BigQuery ML
• Advanced BigQuery Performance and Functionality
• Cloud Dataflow Streaming Features
• Creating a Data Lake
• Introduction to Data Engineering
• Production ML Pipelines and use of Kubeflow
• Introduction to Processing Streaming Data

These modules involve everything the candidate requires for passing the Professional Data Engineer certification exam. Thus, you will not miss anything if you are taking this learning program keenly and apply the required knowledge in an appropriate way. You would end up getting a good score and achieving the Google Professional Data Engineer certification.

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