What you'll learn:
- Deploy serverless applications using Google App Engine , Cloud Functions & Cloud Run
- Learn how to use datastore (NoSql Database) in realistic use-cases
- Microservice and Event driven architecture with practical examples
- Deploying production level machine learning workflows on cloud
- Use Kubeflow for Machine learning orchestration using Python
- Deploy Serverless Pyspark Jobs to Dataproc Serverless and schedule them using Airflow/Composer
Google Cloud platform is one of the fastest growing cloud providers right now . This course covers all the major serverless components on GCP including a detailed implementation of Machine learning pipelines using Vertex AI with Kubeflow and includging Serverless Pyspark using Dataproc , App Engine and Cloud Run .
Are you interested in learning & deploying applications at scale using Google Cloud platform ?
Do you lack the hands on exposure when it comes to deploying applications and seeing them in action?
If you answered "yes" to the above questions,then this course is for you .
You will also learn what are micro-service and event driven architectures are with real world use-case implementations .
This course is for anyone who wants to get a hands-on exposure in using the below services :
Cloud Functions
Cloud Run
Google App Engine
Vertex AI for custom model training and development
Kubeflow for workflow orchestration
Dataproc Serverless for Pyspark batch jobs
This course expects and assumes the students to have :
A tech background with basic fundamentals
Basic exposure to programming languages like Python & Sql
Fair idea of how cloud works
Have the right attitude and patience for self-learning :-)
You will learn how to design and deploy applications written in Python which is the scripting language used in this course across a variety of different services .
