Data Engineering, Big Data, and Machine Learning on GCP

Google Cloud

Embark on a comprehensive journey through Google Cloud's Data Engineering, Big Data, and Machine Learning program. This course equips you with the skills to succeed in the industry and prepares you for the Google Cloud Professional Data Engineer certification. Through a series of modules, you will delve into Google Cloud's essential products, including Dataflow, Pub/Sub, Vertex AI, AutoML, BigQuery, and more.

  • Complete the Coursera Data Engineering Professional Certificate
  • Review recommended resources for the certification exam
  • Explore the Professional Data Engineer exam guide
  • Work on hands-on projects using Qwiklabs
  • Develop practical skills in building and managing data pipelines, data lakes, and data warehouses on Google Cloud

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Data Engineering, Big Data, and Machine Learning on GCP
Course Modules

Enhance your skills in Google Cloud's Data Engineering, Big Data, and Machine Learning program. Explore essential topics, including data-to-AI lifecycle, modernizing data lakes and warehouses, batch data pipelines, resilient streaming analytics, and smart analytics with machine learning and AI.

Google Cloud Big Data and Machine Learning Fundamentals

Identify the data-to-AI lifecycle on Google Cloud and learn about major products of big data and machine learning. Design and build streaming pipelines with Dataflow and Pub/Sub. Explore options to build machine learning solutions with Vertex AI and AutoML.

Modernizing Data Lakes and Data Warehouses with Google Cloud

Understand the differences between data lakes and data warehouses and explore use-cases for each type of storage. Dive into the available solutions on Google Cloud, and learn about the role of a data engineer and the benefits of a successful data pipeline.

Building Batch Data Pipelines on Google Cloud

Review different methods of data loading and processing. Run Hadoop on Dataproc, build data processing pipelines using Dataflow, and manage data pipelines with Data Fusion and Cloud Composer.

Building Resilient Streaming Analytics Systems on Google Cloud

Explore use-cases for real-time streaming analytics, manage data events using the Pub/Sub service, and create streaming pipelines with Dataflow and BigQuery for real-time analysis.

Smart Analytics, Machine Learning, and AI on Google Cloud

Dive into machine learning, AI, and deep learning concepts. Discuss the use of ML APIs on unstructured data, execute BigQuery commands from Notebooks, and create ML models using SQL syntax in BigQuery and AutoML without coding.

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