MLOps: Exhaustive Guide + AWS, GCP, Apple Cases

Learn to deploy ML solutions, Industry best practices and hacks to BOOST your career
What you'll learn
Productionize ML Solutions to Real World Business Problems
Roll out ML Models to Multiple Environments
Learn to Work in AWS Sagemaker
Learn to Work in GCP Vertex AI
Train & Deploy ML Models for Apple Devices
Create a Solid Case to GET PROMOTED in Your Career
Requirements
Basic Python experience
Basic Docker experience
Basic Terminal experience
Description
Would you like to learn best practices of Automation & Deployment for ML models?
Maybe you would also like to practice doing it?

You've come to the right place!

There's no better way to achieve that than by creating a strong theoretical foundation and getting hands dirty by applying newly learnt concepts in practice straight away!

MLOps has been helping me automate & roll out robust, easily maintainable and state-of-the-art ML in IT, Food and Travel industries over the last 6 years.
With the help of modern Cloud Computing and open source software I've brought live dozens of ML research projects, successfully solved very complex Business challenges and even changed the country where I live & work!

Join me in this fun and Industry-shaped course to get new skills and improve your MLOps & Cloud & Business acumen!

By the end of this course you will be able to:

Set up CI & CD pipelines
Package ML models into Docker
Run AutoML locally & in the Cloud
Train ML models for Apple devices
Monitor and Log ML experiments with MLFlow framework
Set up and manage MLOps pipelines in AWS SageMaker
Operate Model Registry & Endpoints in GCP VertexAI
Boost your Career and MLOps studying efficiency

P.S. If you'd like to learn how to deploy your solutions in form of Interactive Analytical Apps, check out my course on Streamlit.

Happy learning!

Who this course is for:
Machine Learning Enthusiasts, Data Scientists, Data Analysts, Developers, AI professionals

More Info