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  • Course No E – 1930
  • PDH Units: 2

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Intended Audience: All Engineers

PDH UNITS: 2

Machine learningย is the study of computer algorithms that improve automatically through experience.ย It is seen as a subset ofย artificial intelligence. Machine learning algorithms build aย mathematical modelย based on sample data, in order to make predictions or decisions without being explicitly programmed to do so. ย Machine learning algorithms are used in a wide variety of applications, such asย email filteringย andย computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks. Course Outline This course narrates Applications and types of Machine Learning. Five categories of Machine learning namely supervised learning, unsupervised learning, reinforcement learning, deep learning and deep reinforcement learning are explained in simple language with suitable examples. Algorithms used for supervised and unsupervised learning are narrated with suitable illustrations. Skills required and platform available for Machine Learning is presented with future scope of work.

Learning Objectives

At the successful conclusion of this course, youโ€™ll be able to identify and discuss:
  • What AI can do?
  • Traditional AI
  • About Machine Learning
  • Classification of Machine Learning
  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Deep learning
  • Deep reinforcement learning
  • Algorithm used
  • Artificial Neural Network
  • Skills required for Machine Learning
  • How to implement Machine Learning

Course No E - 1930
PDH Units: 2

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