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Deep Learning with TensorFlow

Deep learning involves algorithms that are modelled on human brain functions. These algorithms learn from large amounts of data to solve complex problems. For the very first time, UTS is offering this specialised course that explores popular deep learning algorithms in detail. Gain a greater understanding of deep learning techniques using the popular open-source software, TensorFlow.

About this course

Explore popular deep learning algorithms in detail, learn TensorFlow for machine learning applications and how it can be used to solve real-life problems. You will learn how to visually summarise data and use it to produce more compelling stories and cases that are clear and easier for your clients and colleagues to comprehend.

Course structure

The following content will be covered during the course:

  • Introduction to TensorFlow
  • Image classification
  • Sentiment analysis: CNN, RNN
  • Neural machine translation
  • Generative adversarial networks
  • Image generation
  • Summary and conclusions.

Learning outcomes

  • Develop an understanding of deep learning fundamentals
  • Understand how deep learning algorithms can be applied and the background of these algorithms
  • Program in TensorFlow and apply TensorFlow to solve machine learning problems
  • Be able to apply some of the tools available for tackling common deep learning problems
  • Identify any knowledge gaps and prepare for potential further studies in the field of deep learning.

Enrolment conditions

COVID-19 response 

Who is this course for?

This course is intended for anyone who is interested in deep learning and using TensorFlow, from beginners to those with a computer science background who may have already studied coding. Subject matter experts across a range of sectors - from finance, insurance and even aviation will find this class valuable.

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