Google Professional Cloud DevOps Engineer - GCP - Exams
Description
Google Professional Cloud DevOps Engineer
This course is a specialized online training program tailored for individuals aiming to excel in the Google Professional Cloud DevOps Engineer certification. This course provides a series of comprehensive mock exams designed to replicate the environment and format of the actual GCP certification exam, offering learners an authentic exam experience.
This course delves deep into the essential topics and skills required for a DevOps engineer specializing in the Google Cloud Platform (GCP). It covers areas such as CI/CD pipelines, monitoring and logging, infrastructure as code, and site reliability engineering, all within the context of GCP services and tools. The course's structure is aligned with the official exam guide, ensuring that all relevant domains are thoroughly addressed.
Each mock exam includes a variety of question formats, including scenario-based and multiple-choice questions, simulating the types of challenges that candidates will face in the actual exam. Detailed explanations and insights accompany each question, providing learners with a deeper understanding of the underlying principles and best practices in cloud DevOps on GCP.
This course is ideal for existing IT professionals, cloud engineers, and system administrators seeking to validate their expertise in managing and optimizing GCP services. It's also beneficial for those transitioning into DevOps roles and looking to gain a reputable certification in the field. By the end of this course, learners will have enhanced their test-taking skills and gained the confidence needed to tackle the Google Professional Cloud DevOps Engineer certification exam successfully.
Can I retake the practice tests?
Yes, you can attempt each practice test as many times as you like. After completing a test, you'll see your final score. Each time you retake the test, the questions and answer choices will be shuffled for a fresh experience.
Is there a time limit for the practice tests?
Yes, each test includes a time limit of 120 seconds per question.
What score do I need to pass?
You need to score at least 72% on each practice test to pass.
Are explanations provided for the questions?
Yes, every question comes with a detailed explanation.
Can I review my answers after the test?
Absolutely. You’ll be able to review all your submitted answers and see which ones were correct or incorrect.
Are the questions updated frequently?
Yes, the questions are regularly updated to provide the best and most relevant learning experience.
Additional Note: It’s highly recommended that you take the practice exams multiple times until you're consistently scoring 90% or higher. Don’t hesitate—start your preparation today. Good luck!
Who this course is for:
- DevOps Engineers
- Cloud Engineers
- Site Reliability Engineers (SREs)
- System Administrators
- IT Operations Professionals
- Software Developers/Engineers
- Solution Architects
- Technical Project Managers
Instructor
- 4.3 Instructor Rating
- 11,167 Reviews
- 431,417 Students
- 164 Courses
EN
Python Developer/AI Enthusiast/Data Scientist/Stockbroker
Enthusiast of new technologies, particularly in the areas of artificial intelligence, the Python language, big data and cloud solutions. Graduate of postgraduate studies at the Polish-Japanese Academy of Information Technology in the field of Computer Science and Big Data specialization. Master's degree graduate in Financial and Actuarial Mathematics at the Faculty of Mathematics and Computer Science at the University of Lodz. Former PhD student at the faculty of mathematics. Since 2015, a licensed Securities Broker with the right to provide investment advisory services (license number 3073). Lecturer at the GPW Foundation, conducting training for investors in the field of technical analysis, behavioral finance, and principles of managing a portfolio of financial instruments.
Founder at e-smartdata
PL
Data Scientist, Securities Broker
Jestem miłośnikiem nowych technologii, szczególnie w obszarze sztucznej inteligencji, języka Python big data oraz rozwiązań chmurowych. Posiadam stopień absolwenta podyplomowych studiów na kierunku Informatyka, specjalizacja Big Data w Polsko-Japońskiej Akademii Technik Komputerowych oraz magistra z Matematyki Finansowej i Aktuarialnej na wydziale Matematyki i Informatyki Uniwersytetu Łódzkiego. Od 2015 roku posiadam licencję Maklera Papierów Wartościowych z uprawnieniami do czynności doradztwa inwestycyjnego (nr 3073). Jestem również wykładowcą w Fundacji GPW prowadzącym szkolenia dla inwestorów z zakresu analizy technicznej, finansów behawioralnych i zasad zarządzania portfelem instrumentów finansowych. Mam doświadczenie w prowadzeniu zajęć dydaktycznych na wyższej uczelni z przedmiotów związanych z rachunkiem prawdopodobieństwa i statystyką. Moje główne obszary zainteresowań to język Python, sztuczna inteligencja, web development oraz rynki finansowe.
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