Google Data Engineer
Instructor-led Google Cloud-aligned training in Google Data Engineer. Delivered live online by senior practitioners, with hands-on labs and a final assessment. Includes an Skilvi course-completion certificate.
Overview
The Google Data Engineer course equips you with the essential skills to design, build, and operationalize data processing systems on Google Cloud. This course is crucial for professionals looking to leverage data in decision-making and drive business insights through advanced analytics and machine learning.
What you'll learn
- You will be able to design data processing systems using Google Cloud technologies.
- You will be able to implement data pipelines using Google Cloud Dataflow.
- You will be able to manage and optimize data storage solutions with Google Cloud BigQuery.
- You will be able to apply machine learning models to data sets using Google Cloud AI tools.
- You will be able to ensure data quality and security in your data engineering projects.
- You will be able to utilize Google Cloud Pub/Sub for real-time data processing.
- You will be able to monitor and troubleshoot data workflows on Google Cloud.
- You will be able to integrate various Google Cloud services for comprehensive data solutions.
Curriculum
7 modules · outline is indicative and can be tailored to your team.
1Introduction to Google Cloud Data Engineering
- Overview of Google Cloud Platform
- Data Engineering roles and responsibilities
- Introduction to data processing concepts
2Building Data Pipelines with Google Cloud Dataflow
- Understanding Apache Beam and Dataflow
- Developing and executing data pipelines
- Handling streaming and batch data
3Data Storage Solutions with Google Cloud BigQuery
- Introduction to BigQuery architecture
- Loading and querying data in BigQuery
- Optimizing query performance and costs
4Real-Time Data Processing with Google Cloud Pub/Sub
- Setting up Pub/Sub for real-time messaging
- Publishing and subscribing to messages
- Integrating Pub/Sub with Dataflow
5Machine Learning with Google Cloud AI Tools
- Overview of Google Cloud AI and ML services
- Training and deploying machine learning models
- Using AutoML for data insights
6Data Quality and Security Best Practices
- Implementing data validation techniques
- Understanding data security measures
- Regulatory compliance in data engineering
7Monitoring and Troubleshooting Data Workflows
- Using Stackdriver for monitoring
- Debugging data pipeline issues
- Best practices for workflow management
Prerequisites
No prior experience required.
Who should attend
This course is ideal for data analysts, data scientists, and IT professionals seeking to enhance their data engineering skills on Google Cloud.
Certification
Prepares you for the official Google Cloud certification exam.
Skilvi is an independent training provider and is not affiliated with, or endorsed by, Google Cloud. Trademarks are the property of their respective owners.
Frequently asked questions
What is the delivery format of this course?
The course is delivered through live-online sessions led by experienced instructors.
How long is the course duration?
The course typically spans over several weeks, with weekly sessions of 2-3 hours each.
Will I receive a certificate upon completion?
Yes, participants will receive an Skilvi course-completion certificate after successfully completing the course.
Are exam vouchers included with the course?
Exam vouchers for certification exams are available through authorized channels on request.
What are the prerequisites for this course?
No prior experience required.
Pricing on request
- Live online (VILT)
- 24–32 hours
- Hands-on labs & assignments
- Skilvi completion certificate
- Exam voucher on request
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