Course Summary
In this course, you will learn to design, implement, and manage machine learning solutions using AWS. You will master data engineering, model training, and deployment with Amazon SageMaker. Additionally, you will gain proficiency in securing ML environments and automating workflows. This course also prepares you for the AWS Certified Machine Learning – Specialty exam, ensuring you can create scalable, efficient, and secure ML solutions on AWS.
Training Modules:
Module 1: Data Engineering
Module 2: Exploratory Data Analysis
Module 3: Modelling
Module 4: Machine Learning Implementation and Operations
You will learn to:
• Understanding the fundamental concepts of machine learning and deep learning, including supervised and unsupervised learning algorithms.
• Building, training, and deploying machine learning models using AWS services such as Amazon SageMaker, AWS Lambda, and AWS Deep Learning AMIs.
• Implementing data preprocessing and feature engineering techniques to prepare data for machine learning workflows.
• Monitoring, optimizing, and troubleshooting machine learning models to improve performance and accuracy using tools like Amazon CloudWatch and AWS CloudTrail.
• Applying best practices for security, scalability, and cost-effectiveness in machine learning solutions on the AWS platform.
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