This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform
. Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.
Audience:
This course is intended for the following audience:
• 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
Prerequisites
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 as Python
• Familiarity with machine learning and/or statistics
Learning Outcomes
• 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.
Certification:
This course is the first step towards the Professional Machine Learning Engineer certification.