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Data Science & Machine Learning: Naive Bayes in Python (Udemy.com)

Master a crucial artificial intelligence algorithm and skyrocket your Python programming skills

Created by: Lazy Programmer Inc.

Last updated February 2026

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What you will learn

  • Apply Naive Bayes to image classification (Computer Vision)
  • Apply Naive Bayes to text classification (NLP)
  • Apply Naive Bayes to Disease Prediction, Genomics, and Financial Analysis
  • Understand Naive Bayes concepts and algorithm
  • Implement multiple Naive Bayes models from scratch

How it compares

Against the other 461 rated Udemy courses in Data Science on CourseDuck:

  • Rating4.6 out of 5higher than 67% of them
  • Reviews738#187 of 462 by number of reviews
  • Length7.5 hoursshorter than 54% of them
  • Last updatedFebruary 2026more recently than 66% of them

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Course Description

In this self-paced course, you will learn how to apply Naive Bayes to many real-world datasets in a wide variety of areas, such as:

  • computer vision

  • natural language processing

  • financial analysis

  • healthcare

  • genomics

Why should you take this course? Naive Bayes is one of the fundamental algorithms in machine learning, data science, and artificial intelligence. No practitioner is complete without mastering it.

This course is designed to be appropriate for all levels of students, whether you are beginner, intermediate, or advanced. You'll learn both the intuition for how Naive Bayes works and how to apply it effectively while accounting for the unique characteristics of the Naive Bayes algorithm. You'll learn about when and why to use the different versions of Naive Bayes included in Scikit-Learn, including GaussianNB, BernoulliNB, and MultinomialNB.

In the advanced section of the course, you will learn about how Naive Bayes really works under the hood. You will also learn how to implement several variants of Naive Bayes from scratch, including Gaussian Naive Bayes, Bernoulli Naive Bayes, and Multinomial Naive Bayes. The advanced section will require knowledge of probability, so be prepared!

Thank you for reading and I hope to see you soon!


Suggested Prerequisites:

  • Decent Python programming skill

  • Comfortable with data science libraries like Numpy and Matplotlib

  • For the advanced section, probability knowledge is required


WHAT ORDER SHOULD I TAKE YOUR COURSES IN?

  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including my free course)


UNIQUE FEATURES

  • Every line of code explained in detail - email me any time if you disagree

  • Less than 24 hour response time on Q&A on average

  • Not afraid of university-level math - get important details about algorithms that other courses leave out

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Instructor Details

Lazy Programmer Inc.

The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.


Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master's degrees. His first foray into academia led him to pursue computer engineering, with a specialized focus on machine learning and pattern recognition. Undeterred by boundaries, he then ventured into the realm of statistics, exploring its applications in financial engineering.


Recognized as a trailblazer in his field, the Lazy Programmer quickly embraced the power of deep learning when it was still in its infancy. As one of the pioneers, he fearlessly embarked on instructing one of the first-ever online courses on deep learning, catapulting him to the forefront of the industry.


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Reviews

4.6

738 ratings on Udemy

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By Damian Fisher on 11/22/2025

I'm taking this course as a supplement to my university machine learning course that I'm currently enrolled in. I can't express enough how much this has helped. Thank you Lazy Programmer!

By Vivek Daga on 11/26/2024

Easy to understand and effectively teaches how to apply naive bayes algorithm in the real world. Lazy Programmer seems to have a secret to boost students from beginner to advanced quickly.

By Dharmendra Modi on 8/17/2024

The course covers everything in detail till now, and offers the best possible learning experience with theory and code for all lectures. The coding exercises are fun and the challenges in every section develop your skills even better.

By Agnes Lam on 4/9/2024

This is a really great take on a simple machine learning model. It's really practical and covers a wide range of applications in different fields. The advanced section covers all the theory behind Naive Bayes so there is something for everyone in this course. Well done!

By Nang Mwe on 6/11/2023

Great course for beginners! If you don't have any experience with ML this is a good place to start. Lazy Programmer is an awesome instructor and very easy to follow (just don't blame him if you did not meet the prerequisites). If you are looking to take this course to understand what machine learning is all about its a good starting point. After finishing this course I would start building a portfolio of projects. Best way to learn is to practice!

By Sharifa Osman on 4/25/2023

Lazy Programmer is a great instructor. Easy to understand, and not only does he give the knowledge of machine learning, but also the experience and wisdom. Thank you!!

By Paul Roschival on 4/20/2023

This guy is so preachy and he is touting the Q and A and there are like 3 trivial questions asked in Q and A. He is wasting my time with nonsensical advice that a three year old already knows.

By Dusan Perovic on 12/31/2022

High - quality content explained through theory and code on practical examples (datasets). The way how everything was explained and structure is for praise. Full support for author to continue with good work and creating extraordinary contents. This course will impact on me to do further research of the topic of Naive Bayes and implement it practically.

By Dario Acevedo on 12/27/2022

Nice explanation, have the right amount of examples and excercises for the topic and each video contains a summary with what you've learned, a good way to know your overall progress.

By Karin Schenk on 12/19/2022

Lazy Programmer's courses are amazing. Simple but still detailed explanations, easy to follow and he does an amazing job at challenging you to do things yourself. The course is broken up into beginner, intermediate, and advanced parts, which makes it easy for all students to follow along in spite of their level of experience. All of them were great!

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Overall Score : 92 / 100