Rating: 4.7 out of 5
Paid: Yes
Platform: Udemy
Overview
If you’re eager to learn best practices of Automation and ML models Deployment, then this is the course for you! With a strong focus on building a solid theoretical foundation and putting newly learned concepts into practice, this course covers essential skills in MLOps, Cloud Computing, and Business acumen that have proven successful over the past six years in the IT, Food and Travel industries.
By the end of this comprehensive course, you’ll be able to set up CI & CD pipelines, package ML models into Docker, run AutoML locally and 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 and Endpoints in GCP VertexAI, and ultimately boost your career and MLOps studying efficiency. For those interested in deploying interactive analytical apps, check out the Streamlit course as well. Happy learning!
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Skills you’ll learn
- Set up CI and CD pipelines
- Package ML models into Docker
- Run AutoML locally and 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 and Endpoints in GCP VertexAI
- Boost your Career and MLOps studying efficiency
Summary
Dive into the world of MLOps with the expert guidance of instructor Maxim Migutin as he unravels the mysteries of ML Model Deployment and showcases real-life cases from AWS Sagemaker, GCP, and Apple. Consisting of 34 comprehensive lessons and enjoyed by 246 enthusiastic students, this high-value course boasts an impressive rating of 4.7 out of 5 stars – a testament to the remarkable learning experience it offers.
Ready to Take Your Skills to the Next Level?
Don’t miss out on this opportunity to learn from the best in the field.