Upon successful completion of the certificate program, students will be able to: describe how machine learning provides the foundation for artificial intelligence; leverage cognitive services in developing applications; build and derive insights using machine learning models in problem spaces such as classification, regression, and clustering; solve image classification problem using deep learning models such as convolution neural network (CNN); forecast time series data and process sequential data using deep learning models such as recurrent neural network (RNN) and long short term memory (LSTM); frame reinforcement learning problems and solve using algorithms such as dynamic programming, temporal difference learning, deep ‘Q’ learning, policy gradient and actor-critic; apply classical image analysis techniques, such as  edge detection,  watershed and distance transformation as well as K-means clustering to segment a basic dataset; apply deep learning models to solve machine translation and conversation problems; and compete and solve a real-world artificial intelligence challenge.