Machine Learning Implementation and Operations in AWS
Key Takeaways
Designs and implements machine learning solutions in AWS for performance, availability, scalability, resiliency, and fault tolerance
Original Description
Machine Learning Implementation Operations in AWS is the fifth Course in the AWS Certified Machine Learning Specialty specialization. The course has a major focus on designing and implementing machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 1:00-1:30 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.
Module 1: Machine Learning Implementation Operations in AWS-Part 1
Module 2: Machine Learning Implementation Operations in AWS-Part 2
Minimum two year of hands-on experience in architecting, building or running ML/deep learning workloads on the AWS Cloud. By the end of this course, Learners will be able to :
-Design machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance
-Implement appropriate machine learning services and features for a given problem
-Develop machine learning solutions with lab
AI explanation not available for this lesson yet
This lesson is still being prepared for the AI tutor. In the meantime, explore lessons that are ready.
Browse explainer-ready lessons →
More on: AI Systems Design
View skill →Related Reads
📰
📰
📰
📰
The Same Requirement Means Different Things to Security, Architecture, and Operations
Medium · AI
Gemini responsded on what exactly is Abstraction in codding
Medium · Programming
Architectural Breakdown: A Storm Didn't Decide This Battle — A Sergeant Did
Dev.to · Muhammad Hammad
Coding Is Getting Easier. But System Design Still Matters.
Dev.to AI
🎓
Tutor Explanation
DeepCamp AI