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Course Description

In this course, you will use the Maximum Likelihood Estimate (MLE) to approximate distributions from data. Using the Bayes Optimal Classifier, you will learn how the assumptions you make will impact your estimations. You will then learn to apply the Naive Bayes Assumption to estimate probabilities for problems that contain a high number of dimensions. Ultimately, you will apply this understanding to implement the Naive Bayes Classifier in order to build a name classification system.

The following course is required to be completed before taking this course:

  • Problem-Solving with Machine Learning

Faculty Author

Kilian Weinberger

Benefits to the Learner

  • Approximate distributions from data with Maximum Likelihood Estimate (MLE)
  • Use Naive Bayes Assumption to estimate probabilities from high dimensional data
  • Build a name classifier using the Naive Bayes algorithm

Target Audience

  • Programmers
  • Developers
  • Data analysts
  • Statisticians
  • Data scientists
  • Software engineers

Applies Towards the Following Certificates

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Enroll Now - Select a section to enroll in
Type
2 week
Dates
Nov 05, 2025 to Nov 18, 2025
Total Number of Hours
18.0
Course Fee(s)
Regular Price $1,199.00
Section Notes

IMPORTANT COURSE INFORMATION

  • Please note the content in the Machine Learning course curriculum was developed to be completed in sequential order as course concepts build throughout the program. With this in mind, please be sure you are scheduled to complete or have completed the courses in order. For example; CIS531 prior to CIS532, CIS532 prior to CIS533, etc.

  • This program also includes two additional self-paced linear algebra courses to assist you in your coursework. You will be automatically enrolled in the courses and can access them at any time before or during your Machine Learning program. If you need to refresh your linear algebra skills, it is highly recommended that you access these additional resources prior to the start of your first course.

Type
2 week
Dates
Dec 03, 2025 to Dec 16, 2025
Total Number of Hours
18.0
Course Fee(s)
Regular Price $1,199.00
Section Notes

IMPORTANT COURSE INFORMATION

  • Please note the content in the Machine Learning course curriculum was developed to be completed in sequential order as course concepts build throughout the program. With this in mind, please be sure you are scheduled to complete or have completed the courses in order. For example; CIS531 prior to CIS532, CIS532 prior to CIS533, etc.

  • This program also includes two additional self-paced linear algebra courses to assist you in your coursework. You will be automatically enrolled in the courses and can access them at any time before or during your Machine Learning program. If you need to refresh your linear algebra skills, it is highly recommended that you access these additional resources prior to the start of your first course.

Type
2 week
Dates
Dec 31, 2025 to Jan 13, 2026
Total Number of Hours
18.0
Course Fee(s)
Regular Price $1,199.00
Section Notes

IMPORTANT COURSE INFORMATION

  • Please note the content in the Machine Learning course curriculum was developed to be completed in sequential order as course concepts build throughout the program. With this in mind, please be sure you are scheduled to complete or have completed the courses in order. For example; CIS531 prior to CIS532, CIS532 prior to CIS533, etc.

  • This program also includes two additional self-paced linear algebra courses to assist you in your coursework. You will be automatically enrolled in the courses and can access them at any time before or during your Machine Learning program. If you need to refresh your linear algebra skills, it is highly recommended that you access these additional resources prior to the start of your first course.

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