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This professional certificate in Data Engineering incorporates hands-on labs using our Qwiklabs platform. These hands-on components will allow you to apply the skills you learn in video conferencing. The projects will incorporate topics such as Google BigQuery, which are used and configured within Qwiklabs. You can expect to gain hands-on experience with the concepts explained throughout the modules.
This program provides you with the skills you need to advance your data engineering career and recommends training to support your preparation for 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 gain real-world experience through a series of hands-on projects using Qwiklabs.
You'll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and put machine learning models to work.
Upon successful completion of this program, you will earn a certificate of completion to share with your professional network and potential employers.
If you want to become Google Cloud certified and demonstrate your competence in designing and building data processing systems and running machine learning models on the Google Cloud Platform, you will need to register for and pass the official Google Cloud certification exam.
You can find more details on how to sign up and additional resources to support your preparation at cloud.google.com/certifications.
This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). Provides a quick overview of Google Cloud Platform and a deeper look at its data processing capabilities.
At the end of this Data Engineering course, participants will be able to:
The two key components of any data pipeline are data lakes and warehouses. This course highlights the use cases for each type of storage and dives into the data lake and storage solutions available on Google Cloud Platform in technical detail.
Additionally, this course outlines the role of a data engineer, the benefits of a successful data pipeline for business operations, and examines why data engineering should be done in a cloud environment.
Students will gain hands-on experience with data lakes and warehouses on the Google Cloud Platform using QwikLabs.
Data pipelines generally fall under one of the Extra-Load, Extract-Load-Transform, or Extract-Transform-Load paradigms. This course describes which paradigm to use and when for batch data.
Additionally, this course covers various technologies in Google Cloud Platform for data transformation, including BigQuery, running Spark in Cloud Dataproc, pipeline graphs in Cloud Data Fusion, and serverless data processing with Cloud Dataflow.
Students will gain hands-on experience building data pipeline components on Google Cloud Platform using QwikLabs.
*Note: This is a new course with updated content from what you may have seen in the previous version of this specialization. Streaming data processing is becoming increasingly popular as streaming enables companies to get real-time metrics on business operations.
This course covers how to create data streaming pipelines on Google Cloud Platform. Cloud Pub/Sub is described to handle incoming streaming data.
The course also covers how to apply aggregations and transformations to streaming data using Cloud Dataflow and how to store processed records in BigQuery or Cloud Bigtable for analysis.
Students will gain hands-on experience building streaming data flow components on Google Cloud Platform using QwikLabs.
Incorporating machine learning into data pipelines increases the ability of companies to extract insights from their data. This course covers various ways machine learning can be included in data pipelines on Google Cloud Platform, depending on the level of customization required.
For little to no customization, this course covers AutoML. For more personalized machine learning capabilities, this course introduces AI Platform Notebooks and BigQuery Machine Learning. Also, this course covers how to produce machine learning solutions using Kubeflow.
Students will gain hands-on experience building machine learning models on the Google Cloud Platform using QwikLabs.
From the course: "The best way to prepare for the exam is to be proficient in the skills required for the job." This course uses a top-down approach to recognize already known knowledge and skills, and to surface information and skill areas for additional preparation.
You can use this course to help create your own personalized preparation plan. It helps you distinguish between what you know and what you don't know. And it helps you develop and practice the skills required of professionals who do this job.
The course follows the organization of the Examination Guide outline, introducing higher-level concepts, "touchstones," so you can determine whether you feel confident about your knowledge of that area and its dependent concepts, or whether you want to study more.
You will also learn and have the opportunity to practice key job skills, including cognitive skills such as case analysis, identifying technical observation points, and developing proposed solutions. These are job skills that are also exam skills.
You'll also test your basic skills with Activity Tracking Challenge Labs. And you'll have plenty of sample questions similar to those on the exam, including solutions.
The end of the course contains an unscored practice test quiz, followed by a scored practice test quiz that simulates the test-taking experience.
With a Coursera Professional Certificate you could start a new career or change your current career. Today's world is demanding skills and knowledge in technologies that more and more companies need. Learn at your own pace, when and where you want. In a period of less than a year you could acquire a professional certificate, which added to your current profession, could give you substantial added value to your work experience and attract the attention of "head hunters".
The most prestigious universities and the most relevant companies in the world offer professional certificates in alliance with Coursera
Professional certificates are the best way to receive top quality education in the world, at unique values.
Each study offers certification options highly valued by recruiters, or prepare you for official industry certification.
Professional certificates are in-depth studies in high-demand technology skills that you can earn in about 6-10 months.
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