Course Description
You can create and manage an assortment of data processes and network models using GCP. This course will go through the various types, including using a GPU and TensorFlow to create and manage GPU and instances.
Learning Objectives
GCP Network Modeling
- start the course
- define the types of virtual networks and the benefits of each
- specify the process for creating a network
Machine Learning with TensorFlow GPU
- recall the process for using TensorFlow with GPU
- describe the various machine learning APIs and their uses
Data Processing Architecture
- describe Dataflow and how it can be used to create data processing streams
- recognize differences between Pub and Sub message middleware and when to use them
- define the various pipelines for Dataflow processing
- demonstrate the process of creating Dataflow pipelines in GCP
- specify the differences between real-time and batch data processing
Practice: Data Analysis and Processing
- recognize more concepts in analysis of data processing in GCP