Google Certified Professional Data Engineer

Hello Cloud Gurus!Data management, data analytics, machine learning and artificial intelligence are all hot topics. And who does these better than Google? Our Google Certified Professional Data Engineer course will help prepare you for the certification exam so you can take that next step in your Cloud career and demonstrate your proficiency in one of the most in-demand disciplines in the industry today.The primary focus of this course is to prepare you for the GCP Professional Data Engineer certification exam. Along the way you’ll solidify your foundations in data engineering and machine learning, ensuring that by the end of the course you will be able to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies.This course will teach you how to: Design, build and operationalize data solutions Process data streams in real-time Efficiently store and access data in the cloud Use the GCP pre-trained AI APIs (vision, speech and text) Train and operationalize ML models.The Google Cloud Professional Data Engineer is for data scientists, solution architects, devops engineers and anyone wanting to move into machine learning and data engineering in the context of Google. Students will need to have some familiarity with the basics of GCP, such as: storage, compute and security; some basic coding skills (like Python); and a good understanding of databases. You do not need to have a background in data engineering or machine learning, but some experience with GCP is essential. This is an advanced certification and we strongly recommend that students take the Google Certified Associate Cloud Engineer exam before embarking on this course. However, anyone who is motivated and wants to understand how big data and machine learning is done on GCP will still find value with this course.Keep being awesome, Cloud Gurus!

• Introduction
• Data Processing Fundamentals
• Storage and Databases
• Big Data Ecosystem
• Real Time Messaging with Pub/Sub
• Pipelines with Cloud Dataflow
• Managed Spark with Cloud Dataproc
• NoSQL Data with Cloud Bigtable
• Data Analytics with BigQuery
• Exploration with Cloud Datalab
• Visualization with Cloud Data Studio
• Orchestration with Cloud Composer
• Introduction to Machine Learning
• Machine Learning with TensorFlow
• Using Pre-Trained ML Cloud APIs
• Leveraging Auto ML Platform
• Operationalizing Machine Learning Models
• Data Security and Industry Regulation
• Dataprep
• Preparing for the Professional Data Engineer Exam