In MLOps (Machine Learning Operations) Platforms: Amazon SageMaker and Azure ML you will learn the necessary skills to build, train, and deploy machine learning solutions in a production environment using two leading cloud platforms: Amazon Web Services (AWS) and Microsoft Azure. This course is also a great resource for individuals looking to prepare for AWS or Azure machine learning certifications or who are working (or seek to work) as data scientists, software engineers, software developers, data analysts, or other roles that use machine learning.
This course is part of the MLOps | Machine Learning Operations Specialization
Offered By
About this Course
Intermediate experience in working with Python, Git for version control, Docker for containerization and Kubernetes for deployment and scaling.
What you will learn
Apply exploratory data analysis (EDA) techniques to data science problems and datasets.
Build machine learning modeling solutions using both AWS and Azure technology.
Train and deploy machine learning solutions to a production environment using cloud technology.
Skills you will gain
- MLOps
- Machine Learning
- Python Programming
- Microsoft Azure
- Amazon Web Services (Amazon AWS)
Intermediate experience in working with Python, Git for version control, Docker for containerization and Kubernetes for deployment and scaling.
Offered by
Syllabus - What you will learn from this course
Data Engineering with AWS Technology
Exploratory Data Analysis with AWS Technology
Modeling with AWS Technology
MLOps with AWS Technology
About the MLOps | Machine Learning Operations Specialization
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.