Data Modeling

Data Modeling

Data Modeling includes various techniques for modeling the data for storage in databases.

This competency area includes estimating probabilities using Bayesian modeling, understanding Linear regression​, Logistic regression​, and predicting labels to name a few. 

Key Competencies:

  1. Estimate probabilities using Bayesian modeling​ - Take a series of observations and estimate the prevalence of each data type using data science libraries.
  2. Linear regression​ - Predict and determine the linear relationship between independent and dependent variables using data science libraries.
  3. Logistic regression​ - Predict and determine the probability of a binary variable using data science libraries.
  4. Separate features into different domains - Using a support vector classifier, find a hyperplane that best separates features into different domains using data science libraries.
  5. Predict labels using decision tree classifier​ - Predict the class or value of a target variable using simple decision rules and data science libraries.