Upon successful completion of the course, students will be able to: describe how machine learning provides the foundation for AI

Leverage cognitive services in developing app; 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 them 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

Complete and solve a real-world artificial intelligence challenge.