Google Cloud Big Data and Machine Learning Fundamentals

SKU: GCPFBDML

Þessi vara er ekki til á lager og þvi ófáanleg eins og er.

This course introduces the fundamentals of Google Cloud's big data and machine learning solutions. It focuses on the data-to-AI lifecycle, showcasing how to use Google Cloud's infrastructure to design and implement data pipelines and build machine learning models. Learners will explore tools like BigQuery, Dataflow, Pub/Sub, Vertex AI, and AutoML, gaining hands-on experience through labs and real-world scenarios.

Forkröfur

To fully benefit from this course, learners should have:

  • A basic understanding of database query languages such as SQL.
  • Familiarity with data engineering workflows, including extract, transform, load (ETL) processes.
  • A conceptual grasp of machine learning models, particularly supervised and unsupervised learning.

Target Audience

This course is designed for:

  • Data analysts, data scientists, and business analysts beginning their journey with Google Cloud.
  • Individuals responsible for data processing pipeline design, machine learning model development, and data visualization.
  • Executives and IT decision-makers evaluating Google Cloud's big data and AI capabilities.

Nemandi mun læra eftirfarandi

By the end of this course, participants will be able to:

  • Identify the data-to-AI lifecycle and major big data and machine learning products in Google Cloud.
  • Design streaming data pipelines using Dataflow and Pub/Sub.
  • Analyse large datasets at scale with BigQuery and create machine learning models using BigQuery ML.
  • Explore various machine learning solutions on Google Cloud and implement workflows using Vertex AI and AutoML.

Samantekt

Module One: Introduction to big data and machine learning on Google Cloud

  • Overview of Google Cloud's infrastructure and data-to-AI lifecycle.
  • Key products supporting big data and AI.
  • Activities:
    • Lab: Exploring a BigQuery Public Dataset.
    • Quiz.

Module Two: Data engineering for streaming data

  • Managing streaming data with Pub/Sub and Dataflow.
  • Creating data visualizations with Looker and Data Studio.
  • Activities:
    • Lab: Building a streaming data pipeline for real-time dashboard creation.
    • Quiz.

Module Three: Big data analysis with BigQuery

  • BigQuery essentials for large-scale data storage and processing.
  • Introduction to BigQuery ML for custom machine learning models.
  • Activities:
    • Lab: Predicting visitor purchases using BigQuery ML.
    • Quiz.

Module Four: Machine learning options on Google Cloud

  • Overview of machine learning solutions available on Google Cloud.
  • Introduction to Vertex AI for unified ML project management.
  • Activities:
    • Quiz.

Module Five: Machine learning workflow with Vertex AI

  • Understanding the stages of a machine learning workflow: data preparation, model training, and deployment.
  • Practical application using Vertex AI and AutoML.
  • Activities:
    • Lab: Predicting loan risk using AutoML with Vertex AI.
    • Quiz.

Module Six: Course summary and additional resources

  • Review of key concepts and tools.
  • Guidance for continued learning in Google Cloud's big data and machine learning offerings.