Google Cloud Training
4 weeks to complete at 10 hours a week
This specialization provides a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data, and carry out machine learning.
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.
The specialization covers the following topics: - Differentiate between data lakes and data warehouses, and explore use-cases for each type of storage on Google Cloud - Design and build scalable batch data pipelines for high-volume ingestion and transformation - Ingest and manage streaming data using Pub/Sub and Managed Service for Apache Kafka - Build and deploy streaming data pipelines with Dataflow - Implement streaming data solutions for real-time analytics and application serving with BigQuery and Bigtable - Differentiate between ML, AI and deep learning, and discuss the use of ML API's on unstructured data - Create ML models by using SQL syntax in BigQuery and without coding using Vertex AI AutoML
Google Cloud Training is dedicated to helping customers apply Google Cloud technologies to create success. Their teams are committed to providing high-quality, hands-on training to enable learners to design and build data processing systems on Google Cloud Platform.
Upon completion of this specialization, learners will have the skills to design and build data processing systems on Google Cloud Platform, including extracting, loading, transforming, cleaning, and validating data, enabling instant insights from streaming data, and training, evaluating, and deploying machine learning models.
