What you will learn
Understand the roles and responsibilities of a data engineer.
Design and build data processing systems on Google Cloud Platform (GCP).
Build end-to-end data pipelines using GCP tools and services.
Analyze data and carry out machine learning tasks on GCP.
Prepare for the Google Cloud Professional Data Engineer certification.
Program Overview
Modernizing Data Lakes and Data Warehouses with Google Cloud
⏱️8 hours
- Differentiate between data lakes and data warehouses.
- Explore use-cases for each type of storage and the available solutions on GCP.
- Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.
- Examine why data engineering should be done in a cloud environment.
Building Batch Data Pipelines on Google Cloud
⏱️17 hours
- Review different methods of data loading: EL, ELT, and ETL.
- Run Hadoop on Dataproc, leverage Cloud Storage, and optimize Dataproc jobs.
- Build data processing pipelines using Dataflow.
- Manage data pipelines and monitor their performance.
Building Resilient Streaming Analytics Systems on Google Cloud
⏱️ 12 hours
- Design streaming data pipelines using Pub/Sub and Dataflow.
- Implement real-time analytics solutions.
- Ensure reliability and scalability in streaming systems.
- Monitor and troubleshoot streaming data pipelines.
Smart Analytics, Machine Learning, and AI on Google Cloud
⏱️ 12 hours
- Explore Google’s AI and machine learning tools.
- Implement machine learning models using BigQuery ML and Vertex AI.
- Integrate AI solutions into data pipelines.
- Understand the ethical considerations in AI and machine learning.
Get certificate
Job Outlook
Proficiency in data engineering and machine learning on GCP is essential for roles such as Data Engineer, Machine Learning Engineer, and Cloud Data Engineer.
Skills acquired in this specialization are applicable across various industries, including technology, healthcare, finance, and more.
Completing this specialization can enhance your qualifications for positions that require expertise in big data and machine learning on cloud platforms.
Specification: Data Engineering, Big Data, and Machine Learning on GCP
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