AWS Certified Machine Learning - Specialty (MLS-C01): Exploratory Data Analysis

What you'll learn

This course is part of a series, designed to help you prepare for the AWS Certified Machine Learning - Specialty (MLS-C01) exam. The courses in this series are focused on the domains from the exam guide, and we recommend taking them in this order: * AWS Certified Machine Learning - Specialty (MLS-C01): Data Engineering * AWS Certified Machine Learning - Specialty (MLS-C01): Exploratory Data Analysis * AWS Certified Machine Learning - Specialty (MLS-C01): Modeling * AWS Certified Machine Learning - Specialty (MLS-C01): Machine Learning Implementation and Operations * AWS Certified Machine Learning - Specialty (MLS-C01): Exam Preparation In this course, AWS Certified Machine Learning - Specialty (MLS-C01): Exploratory Data Analysis, you’ll learn to prepare, sanitize, and visualize data. First, you’ll explore how to handle missing data, detect outliers, format inconsistent data, and augment imbalanced data. Next, you’ll discover how to extract features from various datasets using feature engineering techniques like encoding, normalization, and dimensionality reduction. Finally, you’ll learn how to effectively visualize data and create various types of graphs and charts. When you’re finished with this course, you’ll have the skills and knowledge to effectively prepare the data needed to develop a high-quality machine-learning model that produces accurate predictions.