Analyze Datasets and Train ML Models using AutoML

The Practical Data Science Specialization's first course, "Analyze Datasets and Train ML Models using AutoML," provides foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text classification algorithms.

Throughout the course, learners will delve into statistical bias detection, feature engineering, and automated machine learning using Amazon SageMaker tools such as Clarify, Data Wrangler, and Autopilot. Practical skills for handling massive datasets in the cloud are emphasized, with a focus on developing and running data science projects efficiently and cost-effectively.

The course is designed for data-focused developers, scientists, and analysts familiar with Python and SQL who want to build, train, and deploy scalable, end-to-end ML pipelines in the AWS cloud.

• Gain foundational concepts for EDA, AutoML, and text classification algorithms
• Learn statistical bias detection, feature engineering, and automated machine learning using Amazon SageMaker tools
• Develop practical skills for handling massive datasets in the cloud
• Master the deployment of data science projects efficiently and cost-effectively in the AWS cloud