Elevate your data engineering skills with the Data Engineering, Big Data and ML on Google Cloud en Español course. Over five weeks, this specialization will equip you with essential knowledge and practical experience in designing and constructing data processing systems within Google Cloud Platform. Through a combination of presentations, demonstrations, and hands-on labs, you will gain expertise in various areas, including processing unstructured data with Spark and AI APIs, building data pipelines, analyzing data, and implementing machine learning functions. Delve into creating resilient streaming analytics systems and harness the power of smart analytics, machine learning, and AI within the Google Cloud environment.
Throughout the course, you will:
This course is ideal for experienced developers responsible for managing big data transformations in their organizations. By enrolling in this specialization, you agree to Qwiklabs' Terms of Service.
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Delve into Google Cloud Big Data and Machine Learning Fundamentals, Modernizing Data Lakes and Data Warehouses with GCP, Building Batch Data Pipelines on GCP, Building Resilient Streaming Analytics Systems on GCP, and Smart Analytics, Machine Learning, and AI on GCP in Español.
Explore the key steps and workflow of machine learning with Vertex AI. Create a machine learning pipeline using AutoML.
Understand the differences between data lakes and data warehouses, and their significance in data pipelines. Learn about the role of data engineers and the benefits of successful data pipelines for business operations. Discover why data engineering should be conducted in a cloud environment.
Review different data loading methods: EL, ELT, and ETL, and when to use each. Utilize Hadoop in Dataproc, Cloud Storage, and optimize Dataproc jobs. Utilize Dataflow for building data processing pipelines. Manage data pipelines with Data Fusion and Cloud Composer.
Gain insight into real-time streaming analysis use cases. Employ Pub/Sub messaging service for managing data events. Write and execute streaming pipelines and perform necessary transformations. Interoperate Dataflow, BigQuery, and Pub/Sub for real-time streaming and analysis.
Understand real-time streaming analysis use cases. Explore the production and consumption aspects of streaming pipelines. Interoperate Dataflow, BigQuery, and Pub/Sub for real-time streaming and analysis.
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