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:
- Processing batch and streaming data by using autoscaling data pipelines on Cloud Dataflow
- Predicting machine models using TensorFlow and Cloud ML
- 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
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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:
- Prebuilt ML Models APIs for Unsaturated Data
- Performing Spark on Cloud Dataproc
- Introduction to Data Engineering
- Cloud Dataflow Streaming Features
- Big Data Analytics with Cloud Al Platform Notebook
- Introduction to Processing Streaming Data
- Serverless Data Processing with Cloud Dataflow
- Creating a Data Lake
- Building a Data Warehouse
- Production ML Pipelines and use of Kubeflow
- Custom Model building Using SQL in BigQuery ML
- Custom Model building Utilizing Cloud AutoML
- Bigtable Streaming Features and High-Throughput BigQuery
- Introduction to Building Batch Data Pipelines
- Handling Data Pipelines with Cloud Composer and Cloud Data Fusion
- Advanced BigQuery Performance and Functionality
- Serverless Messaging Using Cloud Sub/Pub
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
Exam Details
The Google Professional Data Engineer certification exam has the duration of 2 hours. The qualifying test is made up of multiple-select and multiple-choice questions. The exam is available either in Japanese or English. To register for it, you are required to go through the official webpage and pay the fee of $200 plus applicable taxes. While completing the registration process, the potential individuals can choose the preferred method of exam delivery. It can be taken in person at the nearest testing center or online from a remote location.
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