Google Cloud Platform Big Data and Machine Learning Fundamentals
- Offered byGoogle Cloud
Google Cloud Platform Big Data and Machine Learning Fundamentals at Google Cloud Overview
Duration | 11 hours |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Credential | Certificate |
Future job roles | Account Planning, .Net, Black Box Testing, Assistant Vice President - IT Knowledge Banking , E Commerce Analyst |
Google Cloud Platform Big Data and Machine Learning Fundamentals at Google Cloud Highlights
- Presentations, Demonstrations, and Hands-on labs.
- Rich Learning Content
Google Cloud Platform Big Data and Machine Learning Fundamentals at Google Cloud Course details
- Learn advanced big data & machine learning techniques
- This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
Google Cloud Platform Big Data and Machine Learning Fundamentals at Google Cloud Curriculum
Module 1: Introducing Google Cloud Platform
Google Platform Fundamentals Overview.
Google Cloud Platform Big Data Products.
Module 2: Compute and Storage Fundamentals
CPUs on demand (Compute Engine).
A global filesystem (Cloud Storage).
CloudShell.
Lab: Set up a Ingest-Transform-Publish data processing pipeline.
Module 3: Data Analytics on the Cloud
Stepping-stones to the cloud.
Cloud SQL: your SQL database on the cloud.
Lab: Importing data into CloudSQL and running queries.
Spark on Dataproc.
Lab: Machine Learning Recommendations with Spark on Dataproc.
Module 4: Scaling Data Analysis
Fast random access.
Datalab.
BigQuery.
Lab: Build machine learning dataset.
Module 5: Machine Learning
Machine Learning with TensorFlow.
Lab: Carry out ML with TensorFlow
Pre-built models for common needs.
Lab: Employ ML APIs.
Module 6: Data Processing Architectures
Message-oriented architectures with Pub/Sub.
Creating pipelines with Dataflow.
Reference architecture for real-time and batch data processing.
Module 7: Summary
Why GCP?
Where to go from here
Additional Resources