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.
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This course is part of the following program(s)
1. Applied Data Analytics
Why This Course?
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
Introduction to Machine Learning
Preprocessing for Machine Learning in Python (Date preprocessing, Standardizing Data, Feature Engineering, Feature Selection)
Unsupervised Learning in Python
Instructor-led online lectures