Here are the links to the storage and data-based documentation. We recommend that you know the basic information about each service, the key features, performance, reliability, and best practices. Also, review how to control access and security in each. Analytics and data processing documentation. You need to know what each of these services contributes to an overall data engineering solution. These are the links to the machine-learning documentation. Same level of detail for the pre-train models. Did you know that the Cloud Vision API doesn't just recognize objects and images, but can also give you back a color palette and composition information? If you didn't know that, then it's a good indicator of something you need to study. As a professional data engineer, you need to be prepared by knowing what options are available. Machine-learning, clearly that's going to be a component of many or most data engineering solutions in the future. So you need to know quite a bit about it. Here is some of the important infrastructure services. You really need to know Stackdriver because every data engineering solution is going to need to be monitored and maintained. Links to our training resources. That's instructor-led training, lab based training on QuickLabs, and on-demand video based training on Coursera. The professional data engineer exam is specifically related to the data engineer track. For example, in the data analysts track, there is a great class called data to insights that covers in detail how to use BigQuery. That class is not part of the data engineering track, so you would not need that class for this exam. The data engineer practice exam will familiarize you with types of questions you may encounter on the certification exam and help you determine your readiness or if you need more preparation and or experience. Successful completion of the practice exam does not guarantee you will pass the certification exam as the actual examines longer and covers a wider range of topics. For a full list of the topics you could be tested on, see the exam guide. There's no limit to the number of times you can take this practice exam. You can't save your progress. If you close the practice exam window, you must start from the beginning. There's no time limit for the practice exam, but we recommend completion in 45 minutes or less. This practice exam is available in English and Japanese. This advanced level quest is unique amongst the other QuickLabs offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer certification. From BigQuery to Dataproc to TensorFlow, this quest is composed of specific labs that will put your GCP data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you'll need other preparation too. The exam is quite challenging and external studying, experience, and our background in cloud data engineering is recommended. Thanks for taking the course preparing for the professional data engineer examination. We hope you enjoyed the course and feel better prepared to attempt the exam. Please fill out the evaluation. Let us know what we got right and what we can improve. Best of luck on the exam.