jupyter-notebook

Course: Missing Data Handling: Imputation

By detecting and exploring missing values in datasets, you can enrich them through data imputation. In this way, you can run analyses with better information. This course teaches you how to treat variables and run the appropriate imputation method for your data set.

Course: Missing Data Handling: Detection and Exploration

In data science, you will always encounter incomplete datasets you must deal with. This course teaches you how to address missing values and find relationships between them. Execute the best treatment to your data with missing values, eliminating or imputing them.

Course: Exploratory Data Analysis

Your career in data science requires understanding the nature of data and its distribution and exploring it using statistical analysis or visualization tools. Through an EDA, you can propose the most appropriate model to address the questions of your projects.