This program provides the skills you need to advance your career in data engineering and provides a pathway to earn the industry-recognized Google Cloud Professional Data Engineer certification. Through a combination of presentations, demos, and labs, you'll enable data-driven decision making by collecting, transforming, and publishing data; and you'll gain real world experience through a number of hands-on Qwiklabs projects that you can share with potential employers. You'll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and operationalizing machine-learning models. For learners looking to get certified, this program will also provide sample questions similar to those on the exam, including solutions and practice exam quizzes that simulate the exam-taking experience. Upon successful completion of this program, you will earn a certificate of completion to share with your professional network and potential employers. If you'd like to earn your Google Cloud certification, you will need to register for and pass the certification exam. Please note that this program helps equip you with the skills you need to take the certification exam, but the certification and certification fee is not included in the cost of this training program.
Профессиональная сертификация 'Data Engineering with GCP'
Advance your career in data engineering.
от партнера
Чему вы научитесь
Learn the skills needed to be successful in a data engineer role
Prepare for the Professional Data Engineer certification
Learn about the infrastructure and platform services provided by Google Cloud Platform
Учащиеся, которые проходят продукт ''Professional Certificate'
- Data Engineers
- Data Scientists
- Technical Leads
- Technical Solutions Engineers
- Chief Technology Officers (CTOs)
Что такое профессиональная сертификация?
Получайте нужные для работы навыки
Если вы ищите новую работу или хотите сменить род деятельности, освойте новую профессию и получите профессиональный сертификат Coursera. Учитесь в собственном темпе где и когда угодно. Зарегистрируйтесь сегодня и начните новый карьерный путь с 7-дневным бесплатным пробным периодом. Приостановить обучение или завершить подписку можно в любой момент.
Практические проекты
Примените свои навыки для выполнения практических проектов и создайте портфолио, которое продемонстрирует потенциальным работодателям вашу готовность к работе. Чтобы получить сертификат, вам нужно успешно завершить проекты.
Получите документ, который подтверждает вашу квалификацию
Завершив все курсы в программе, вы получите сертификат, которым можно делиться с коллегами по отрасли, а также доступ к профессиональным ресурсам, которые помогут начать новую карьеру. Многие профессиональные сертификации признаются работодателями-партнерами, а другие помогают подготовиться к сертификационному экзамену. Подробная информация доступна на страницах профессиональных сертификаций.
Профессиональная сертификация включает несколько курсов: 6
Google Cloud Platform Big Data and Machine Learning Fundamentals
This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform • Employ BigQuery and Cloud Datalab to carry out interactive data analysis • Choose between Cloud SQL, BigTable and Datastore • Train and use a neural network using TensorFlow • Choose between different data processing products on the Google Cloud Platform Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following: • A common query language such as SQL • Extract, transform, load activities • Data modeling • Machine learning and/or statistics • Programming in Python Google Account Notes: • Google services are currently unavailable in China.
Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform
This 1-week, accelerated course builds upon previous courses in the Data Engineering on Google Cloud Platform specialization. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to create and manage computing clusters to run Hadoop, Spark, Pig and/or Hive jobs on Google Cloud Platform. You will also learn how to access various cloud storage options from their compute clusters and integrate Google’s machine learning capabilities into their analytics programs. In the hands-on labs, you will create and manage Dataproc Clusters using the Web Console and the CLI, and use cluster to run Spark and Pig jobs. You will then create iPython notebooks that integrate with BigQuery and storage and utilize Spark. Finally, you integrate the machine learning APIs into your data analysis. Pre-requisites • Google Cloud Platform Big Data & Machine Learning Fundamentals (or equivalent experience) • Some knowledge of Python
Serverless Data Analysis with Google BigQuery and Cloud Dataflow
This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals • Experience using a SQL-like query language to analyze data • Knowledge of either Python or Java Google Account Notes: • Google services are currently unavailable in China.
Serverless Machine Learning with Tensorflow on Google Cloud Platform
This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models. OBJECTIVES This course teaches participants the following skills: ● Identify use cases for machine learning ● Build an ML model using TensorFlow ● Build scalable, deployable ML models using Cloud ML ● Know the importance of preprocessing and combining features ● Incorporate advanced ML concepts into their models ● Productionize trained ML models PREREQUISITES To get the most of out of this course, participants should have: ● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience ● Basic proficiency with common query language such as SQL ● Experience with data modeling, extract, transform, load activities ● Developing applications using a common programming language such Python ● Familiarity with Machine Learning and/or statistics Google Account Notes: • Google services are currently unavailable in China.
О Google Cloud
Часто задаваемые вопросы
Какие правила возврата средств?
Можно ли зарегистрироваться только на один курс?
Да! Чтобы начать, нажмите карточку интересующего вас курса и зарегистрируйтесь. Зарегистрировавшись, вы можете пройти курс, чтобы получить сертификат, ссылкой на который можно делиться с другими людьми. Просто ознакомиться с содержанием курса можно бесплатно. При подписке на курс, входящий в сертификацию, вы автоматически подписываетесь на всю сертификацию. Ход учебы можно отслеживать в панели управления учащегося.
Действительно ли это полностью дистанционный курс? Нужно ли мне посещать какие-либо занятия лично?
Это полностью дистанционный курс, потому вам не нужно ничего посещать. Все лекции, материалы для самостоятельного изучения и задания доступны всегда и везде по Интернету и с мобильных устройств.
How long does it take to complete the Professional Certificate?
This Professional Certificate is designed to be completed in one and a half months at 5 hours per week.
What background knowledge is necessary?
To get the most out of this program, learners should have basic proficiency with a common query language such as SQL; experience developing applications using a common programming language such as Python; experience with data modeling, extract, transform, load activities ; and familiarity with machine learning and/or statistics.
Do I need to take the courses in a specific order?
We strongly recommend you take these courses in order, beginning with Big Data and Machine Learning Fundamentals. This is especially important when completing the Qwiklabs projects, as these hands-on labs build upon the work you complete in preceding courses.
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