Machine Learning Algorithms

Member Price: $499.00
Non-Member Price: $549.00

Course Description 

This introductory course on machine learning algorithms provides students with a solid understanding of the core principles, applications, and limitations of machine learning, differentiating it from traditional programming approaches. Through instructor-led coding demonstrations, students will explore various supervised and unsupervised learning algorithms within prominent frameworks. The course aims to empower students with the knowledge to analyze and select appropriate machine learning algorithms and techniques to tackle real-world challenges, without the need for hands-on practice.

This is an asynchronous, self-paced course with no live instructor. The schedule is flexible and allows learners to complete coursework and assignments at their own pace and time. 

In the Brightspace account select Awards from the Course Tools drop-down menu in the navigation bar to view your certificate. When you have completed the course, please select the Course Feedback Survey link to take the anonymous survey. The survey should not take more than 5 minutes to complete. Your feedback will help shape the overall design of this and other online courses offered by Purdue University. When you have completed the courses, please select the Course Feedback Survey link to take you to the anonymous survey. The survey should not take more than 5 minutes to complete.

Learning Outcomes

At the end of this course, you should be able to:

  • Describe the capabilities 
  • Analyze a variety of supervised and unsupervised machine learning algorithms using prominent frameworks.
  • Integrate machine learning knowledge to address real-world challenges by choosing appropriate algorithms and techniques.

 

Module Topic & Readings
1

Intro to Machine Learning

Understand and Build Machine Learning Models

Supervised Machine Learning Algorithms

Logistic and Linear Regression

3

Understanding Machine Learning Algorithms

Applications of Clustering

4

Capstone Project

 

 

 

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