Deep Learning is an advancement in machine learning technology that uses neural networks for building prediction models. In this course, students use TensorFlow, an open-source and industry standard library for machine learning developed by Google Brain.



TensorFlow allows distribution of computation across CPUs and multiple GPUs on a single computer—an enhancement that enables development of high-performance prediction models.



Students will build prediction models of different complexities, from simple linear logistic regression to convolutional neural network (CNN) and recurrent neural network (RNN) with long Short-term memory (LSTM).



By the end of the class, students have a working deep learning environment and sample projects. The class prepares students to pursue a career in data sciences.

Topics Include:

• Deep learning and TensorFlow


• Multilayer perceptrons


• Advanced multilayer perceptrons


• Convolutional neural networks


• Recurrent neural networks


• RNN - prediction with multilayer perceptron


• RNN - prediction with long short term memory networks

Skills Needed: Moderate level of computer programming ability in Python and basic understanding of machine learning models.