Machine Learning

ML I | ML II


Although machine learning is primarily a theoretical and statistical field, practical programming is an essential component of implementing and experimenting with machine learning models. Therefore, courses listed here are considered programming courses for the purposes of best practices and version control usage.



Machine Learning I

This course will introduce the student to terms and concepts related to artificial intelligence (AI), including augmented intelligence, machine learning, deep learning, neural networks, and natural language processing. The material will be presented using an application-oriented approach, focusing on the techniques and methods and the statistics of these methods. The language of instruction will be Python, and Python libraries will be used for implementing the machine learning models.

The topics covered in the course will include but are not limited to:

  • Data analysis.
  • Data preparation.
  • Statistical analysis.
  • Classical AI.
  • Modern machine learning.
  • Natural Language Processing.
  • AI model development using machine neural networks.
  • AI model analysis.
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Machine Learning II

  • Coming Soon
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