Machine learning with business applications.
Survey of statistical and machine learning algorithms and techniques including the machine learning framework, regression, classification, regularization and reduction, tree-based methods, unsupervised learning, and fully-connected, convolutional, and recurrent neural networks.
Implement machine learning models with open-source software for data science.
Explore data and learn from data, finding underlying patterns useful for data reduction, feature analysis, prediction, and classification.