AWS Machine Learning

What you will learn

• You will learn how to build complete machine learning solutions on AWS, including data preparation, exploratory data analysis, feature engineering, model development and training, deep learning, ML infrastructure, model deployment, monitoring, and optimization. The course also covers AWS machine learning services, data security and privacy, responsible AI, and practical approaches for developing scalable and reliable ML solutions in real-world cloud environments.

This course includes

• Comprehensive video lessons covering AWS machine learning services, data engineering, exploratory data analysis, feature engineering, model development, deep learning, ML infrastructure, model deployment, monitoring, data security and privacy, and responsible AI. The course also includes practical concepts and real-world approaches for building, deploying, and managing scalable machine learning solutions on AWS.

Requirements

• Basic knowledge of cloud computing, data science, or machine learning is recommended. Learners should have a general understanding of AWS services and basic programming concepts, preferably Python. Familiarity with data preparation, statistics, and machine learning fundamentals will help learners understand the advanced AWS ML concepts more effectively.

Description

Who this course is for

• This course is designed for aspiring and experienced data scientists, machine learning engineers, cloud professionals, AI developers, data engineers, and IT professionals who want to build and deploy machine learning solutions on AWS. It is also suitable for learners who want practical knowledge of AWS ML services and the complete machine learning lifecycle.