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Machine Learning

Course

Description

Machine learning creates artificial intelligence applications by training computers to make predictions based on patterns in data. Through hands-on exercises, this course will teach you how to prepare data and apply the algorithms used to build predictive data models. You’ll learn how to test the models you create and use the results to improve their accuracy, so you’ll be able to develop task-specific, problem-solving machine-learning solutions.

Key takeaways

  • Preprocess complex datasets and engineer features for machine-learning analysis
  • Build regression and classification models using Python tools
  • Distinguish among supervised, unsupervised and ensemble approaches
  • Measure model performance and interpret results
  • Build a business case for applying machine learning to a real-world problem
There are no upcoming dates at this time.

Requirements

  • Prerequisite course: Programming for Data Analytics (CEBD 1160)
  • English language proficiency to understand and engage in course content
  • A computer with a stable internet connection, headphones, and a microphone