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Deep Learning Using TensorFlow

This course is an elective in the Machine and Deep Learning Specialized Study Program.

Course Description

Deep Learning is a branch of Artificial Intelligence (AI) that is based on the architecture of Neural Networks. When the number of hidden layers in a neural network is extended, it becomes a ‘Deep Learning’ Neural Network. Applications of Deep Learning include object recognition in images, natural language processing, and human speech recognition. Deep Learning applications are found in virtually all industries including manufacturing, pharmaceuticals, medical, information security, etc. This course will start out by covering advanced concepts of Neural Networks and Deep Learning and will continue with how these concepts can be applied using TensorFlow, a Python-based low-level library. TensorFlow is a great ML tool and makes machine learning faster and easier. The procedure of installing TensorFlow and Keras will be explained before moving into more complex activities such as ML modeling methods testing (estimation and classification). The architecture of GPU (Graphics Processing Units) and TPU (Tensor Processing Units) will also be addressed. Prerequisite(s): I&C SCI X426.64 Introduction to Programming with Python AND I&C SCI X426.75 Tools and Techniques for Machine Learning.

Prerequisite(s): I&C SCI X426.64 Introduction to Programming with Python AND I&C SCI X426.75 Tools and Techniques for Machine Learning.

NOTE: This course includes live sessions via Zoom.   A device with audio and visual will be needed to participate.  The following student guide provides additional resources/information on how to use and access your courses Zoom sessions.

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  • Details
  • $805
  • Reg#: 00296
  • ID/Units: I&C SCI X426.78  (2.50)
    ( Section 1 )
  • Quarter: SUMMER 2021