This course introduces you to additional topics in Machine Learning that complement essential tasks, including forecasting and analyzing censored data. You will learn how to find analyze data with a time component and censored data that needs outcome inference. You will learn a few techniques for Time Series Analysis and Survival Analysis. The hands-on section of this course focuses on using best practices and verifying assumptions derived from Statistical Learning.
Who should attend
This course targets aspiring data scientists interested in acquiring hands-on experience with Time Series Analysis and Survival Analysis.
Course Prerequisites
To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Supervised Machine Learning, Unsupervised Machine Learning, Probability, and Statistics.
Additional information
PLEASE NOTE: It may take 2-3 business days for your course access to be activated. You will receive an email from us with all necessary details.