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The first module of this course introduces some fundamentals of AI and ML including their relationship, different types of data, training and testing, common types of learning techniques (supervised and unsupervised learning) and applications (regression, classification, and clustering). The second module introduces some commonly used machine learning algorithms. Students will understand the fundamentals of AI and ML and implement linear regression, logistic regression, Support Vector Machine (SVM) and K-Means clustering algorithms with Scikit-learn machine learning library. 

Learning Description

After completing this online, asynchronous course, students will

  • understand the fundamentals of AI and ML
  • implement linear regression, logistic regression
  • implement Support Vector Machine (SVM) and K-Means clustering algorithms with Scikit-learn machine learning library

Target Audience

Students with interest in machine learning with Scikit-learn

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Title
Using SciKit-learn for Artificial Intelligence and MachineLearning
Type
Online, self paced
Dates
Sep 01, 2025 to Aug 31, 2026
Fee(s)
Reg Fee non-credit $0.00
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