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Master Cloud-Based Machine Learning on AWS
This course will teach critical skills to design and deploy scalable ML solutions. The core skills covered are:
It offers hands-on AWS training that is ideal for software developers, data scientists, ML engineers, and DevOps professionals, this course blends theory with practical projects to help you design production-ready ML architectures, automate CI/CD pipelines for efficient deployment, implement security best practices for cloud-based systems.
You can find additional resources here: https://bitbucket.org/awsdevguru/awsmlassoc/src/main/
Related Learning:
Skill Level:
Course requirement:
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Module 1: Data Preparation for Machine Learning
Lesson 1: Data Ingestion and Storage Basics
Lesson 2: Data Transformation and Feature Engineering with SageMaker
Lesson 3: Preparing Data for Modeling
Module 2: ML Model Development
Lesson 4: Choosing and Training Models in SageMaker
Lesson 5: Model Evaluation and Bias Detection
Module 3: Deployment and Orchestration of ML Workflows
Lesson 6: Deploying Models with SageMaker
Lesson 7: Automating ML Workflows with SageMaker Pipelines
Module 4: ML Solution Monitoring, Maintenance, and Security
Lesson 8: Monitoring and Optimizing ML Solutions
Lesson 9: Securing ML Models and Data in SageMaker
Module 5: Exam Preparation and Strategy
Lesson 10: Exam Strategies and Practice