Course Details

Machine Learning

course Self-paced

This course first introduces various preprocessing steps and feature selection/engineering methods needed for machine learning algorithms. Students will learn different supervised and unsupervised machine learning approaches for creating predictive models. Finally, the students will learn the basics of model optimization and validation techniques.

Buy this course

CAD 450

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Duration

20 hours

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Prerequisite

None

Why This Course?

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Upgrading Skills

After completing this course, students will be able to:

  • Learn the data preprocessing, feature engineering, feature selection techniques

  • Learn the concepts and develop machine learning models. 

  • Learn model validation and optimization techniques

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Employment Opportunity

  • Data analyst

  • Data Engineer

  • Data scientist

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Main Topics

  • Introduction to Machine Learning

  • Preprocessing for Machine Learning in Python (Date preprocessing, Standardizing Data, Feature Engineering, Feature Selection)

  • Supervised Learning

  • Unsupervised Learning in Python

  • Model Validation

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Training Methods

  • Instructor-led online lectures

  • Simulated/Offline labs

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