This course teaches participants the following skills:
Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.
Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.
Employ BigQuery and Cloud Datalab to carry out interactive data analysis.
Train and use a neural network using TensorFlow.
Employ ML APIs.
Choose between different data processing products on the Google Cloud Platform.
Interact with Google Cloud Platform services
Prerequisite
To get the most of out of this course, participants should have:
Basic proficiency with common query language such as SQL
Experience with data modeling, extract, transform, load activities
Developing applications using a common programming language such Python
Familiarity with Machine Learning and/or statistic
Target Audience
This class is intended for the following:
Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform.
Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports.
Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists.
Course Curriculum
Module 1: Course Introduction
Module 2: Big Data and Machine Learning on Google Cloud
Module 3: Data Engineering for Streaming Data
Module 4: Big Data with BigQuery
Module 5: Machine Learning Options on Google Cloud
Module 6: The Machine Learning Workflow with Vertex AI
