This course introduces advanced Machine Learning theories, methodologies, algorithms, application tools, and programming tools.

CILO-1: Apply machine learning algorithms, such as supervised/unsupervised learning, mixture models and deep learning techniques in solve real-world scenarios. CILO-2: Assess and compare correlations in data sets and quantify uncertainties in the selection of effective data for Machine Learning algorithms. CILO-3: Construct a machine learning model pipeline to address different classification problems. CILO-4: Evaluate the limitations of different types of machine learning algorithms and choose the appropriate approach for different real-world scenarios.