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409 Best + Free Machine Learning Courses & Certificates [2026]

409 courses compared 156 over 10 hours long 5.0 from 1 reader ratings Updated October 5, 2026

Ranked by Michael Kuhlman, CourseDuck's founder, from student reviews across every provider. How we rank · Embed this list

Our guide: The 5 Best Machine Learning Courses in 2026

Our top picks

  • Machine Learning A-Z [2026]: ML, DL, AI with AWS, Python & R [Udemy] - Best Paid Course
  • Python for Data Science and Machine Learning Bootcamp [Udemy] - Editor's Choice
  • Complete A.I. & Machine Learning, Data Science Bootcamp [Udemy]
  • The Top 5 Machine Learning Libraries in Python [Udemy]
  • The Complete Python Developer [Udemy]
  • Machine Learning, Data Science & AI Engineering with Python [Udemy]
  • Machine Learning for Absolute Beginners - Level 1 [Udemy]
  • Complete Data Science,Machine Learning,DL,NLP Bootcamp [Udemy]
  • Artificial Intelligence & Machine Learning for Business [Udemy]
  • Machine Learning by Stanford [Coursera] - Best Course Overall

About the best Machine Learning courses

CourseDuck compares the 409 Machine Learning courses listed here from 26 providers, 178 of them free, and ranks them from the 1.2 million ratings and reviews their students have left, with the price, length and level of each one side by side. No course pays to be listed or ranked. As featured on Harvard EDU, Stackify and Inc. How we rank

Frequently asked questions

  • Udemy and Eduonix are best for practical, low cost and high quality Machine Learning courses.
  • Coursera, Udacity and EdX are the best providers for a Machine Learning certificate, as many come from top Ivy League Universities.
  • YouTube is best for free Machine Learning crash courses.
  • PluralSight, SkillShare and LinkedIn are the best monthly subscription platforms if you want to take multiple Machine Learning courses.
  • Independent Providers for Machine Learning courses & certificates are generally hit or miss.
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Average
$157,676 a year
Middle half earn
$129,000 to $187,500 25th to 75th percentile
Full range
$108,000 to $196,000

Share of US job postings in each pay band; the dark bar holds the average, the striped bars the 25th and 75th percentiles. Source: ZipRecruiter salary data, gathered when this guide was first published in October 2026.

Yes and No. Certified Machine Learning developers on average make more money. Having a Machine Learning certificate greatly increases the chance of landing an interview and can open otherwise closed doors. Coursera, Udacity and EdX offer excellent certificate options for impressing your future employers. Eduonix, Udemy and several other providers offer certificates, but they aren't as reputable. If you have a Computer Science Degree, certificates are not as important. Still, many employers won't care about certificates, but rather your interview skills, experience and/or skills assessment.

Provider

University

Tags

Rating

Duration

Difficulty

Publication Year

Language

409 Filtered Courses
Python for Data Science and Machine Learning Bootcamp
provider
Editor's Choice

3

Python for Data Science and Machine Learning Bootcamp (2020)

4.5

Udemy's Bestseller-badged Python data science bootcamp, taking you from pandas through scikit-learn to a first neural net in about 25 hours, if you can live with 2020-era tooling.

Best for: People who already code a little and want one course covering pandas, plotting and every classic ML algorithm.

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Pros
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Cons
    • A code notebook for every lecture, so students run the code rather than just watch it
    • Pandas section and the visualization libraries are singled out by reviewers as highlights
    • Covers regression, trees, SVMs, k-means, NLP, neural nets and Spark in one place
    • Q&A section that reviewers call very useful when they get stuck
    • Last updated May 2020; Plotly/Cufflinks, PySpark and some Seaborn calls no longer work as shown
    • Long on videos, short on practice: one quiz and no coding exercises across 165 lectures
    • Decision trees and the deep learning section feel rushed to several reviewers
Complete A.I. & Machine Learning, Data Science Bootcamp
provider

4

Complete A.I. & Machine Learning, Data Science Bootcamp (2026)

4.7

Andrei Neagoie and Daniel Bourke's 44 hour ramp from Python basics to TensorFlow 2, built around two milestone projects and holding a 4.7 rating from about 31,000 students.

Best for: Complete beginners, no math or coding required, who want one long guided path to a first deep learning project.

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Pros
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Cons
    • Two milestone projects, a classification task and a time series model, with all notebooks provided on GitHub
    • Two separate Python sections so non-programmers can start from zero and coders can skip straight to pandas
    • Refreshed in February 2026, with 384 lectures and 61 articles spread across 20 sections
    • Reviewers call the teaching engaging and fun to watch, with a new-hire framing that keeps lessons focused
    • Unsupervised learning is in the blurb, but one low-star reviewer says it is missing and the course feels incomplete
    • Only two quizzes and one coding exercise across 44 hours, so practice is mostly watch and retype
    • Informal chatter and lightly explained concepts frustrate reviewers who wanted more depth
The Top 5 Machine Learning Libraries in Python
provider

5

The Top 5 Machine Learning Libraries in Python (2025)

4.6

A free, 100-minute tour of pandas, NumPy, scikit-learn, matplotlib and NLTK that shows what each library is for before anyone commits to a long machine learning bootcamp.

Best for: Total beginners who want to know what each Python ML library does before paying for a full bootcamp.

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Pros
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Cons
    • Free and only 100 minutes long, so it fits in a single evening
    • Opening terminology section that reviewers say clears up most of the early confusion
    • Annotated Jupyter notebook included so students can run the code while watching
    • Refreshed in April 2025, unusual for a free course first published in 2017
    • Surface level only; three-star reviewers say nobody could build a model from this alone
    • Some reviewers say it jumps between topics rather than teaching one library properly
    • No coding exercises, and the final bonus lecture is a pitch for the paid course
The Complete Python Developer
provider

7

The Complete Python Developer (2026)

4.6

A 31-hour beginner Python course that goes from basics into scripting, scraping, web development and a short machine learning section, all taught by one instructor.

Best for: Complete beginners who want one course that samples scripting, scraping, web apps and a little machine learning.

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Pros
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Cons
    • Reviewers call the explanations clear and easy to follow for a first language
    • One reviewer says it explains why Python behaves as it does, not just syntax
    • After the core language, it samples scripting, scraping, web and machine learning
    • Refreshed in August 2026, and the description targets Python 3.13
    • Some reviewers say tooling and practices feel dated, for example no uv
    • At least one student hit errors following along on a newer Python version
    • A few reviewers say it stays high level and is thin on fundamentals depth
Machine Learning, Data Science & AI Engineering with Python
provider

8

Machine Learning, Data Science & AI Engineering with Python (2026)

4.6

Frank Kane's 20-hour survey runs from a Python and stats refresher through classical ML to GPT, RAG and LLM agents, refreshed August 2026 and rated 4.6 by nearly 37,000 students.

Best for: Working programmers who want one broad, current tour of machine learning plus generative AI before picking a specialty.

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Pros
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Cons
    • Covers GPT, the OpenAI API, RAG and LLM agents, with the content refreshed in August 2026
    • Reviewers say the instructor speaks slowly and clearly and the setup steps and notebooks just work
    • About 20 hours across 148 lectures, from a stats refresher to Spark MLlib and deep learning
    • 4.6 stars from nearly 37,000 reviews, roughly 90 percent of them 4 or 5 stars
    • Several reviewers say the instructor reads from notes rather than building intuition
    • A long statistics and probability stretch comes before the real projects begin
    • Some download links have gone stale, and there is no full LLM or agents project
Machine Learning for Absolute Beginners - Level 1
provider

9

Machine Learning for Absolute Beginners - Level 1 (2026)

4.5
Learn the Fundamental Concepts of Artificial Intelligence and Machine Learning as the Next Game-Changing Technology

iconWhat You'll Learn

  • Artificial Intelligence, Machine Learning and Deep Learning
  • Applied vs. Generalized AI
  • Features, Labels, Examples
  • The Process of Training a Model
  • Under-fitting and Over-fitting
  • Supervised/Unsupervised Learning
  • Classification and Regression
  • Clustering and Dimension Reduction
  • Reinforcement Learning
  • Generative AI
Complete Data Science,Machine Learning,DL,NLP Bootcamp
provider

10

Complete Data Science,Machine Learning,DL,NLP Bootcamp (2026)

4.5

A 100 hour path from Python basics to MLOps with Krish Naik: statistics, classic ML algorithms, two deployment projects and an NLP finish, with plenty of math.

Best for: Python-literate beginners who want one long path from statistics and ML math to Docker and cloud deployment.

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Pros
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Cons
    • Explains why each algorithm exists and the math behind it, reviewers say
    • Two long end to end projects cover Docker, AWS, Azure, MLflow and ETL pipelines
    • Updated in August 2026, with 436 lectures and 20 coding exercises
    • Reviewers say lectures stay easy to follow even at 1.75x or 2x speed
    • Some topics feel rushed, and libraries get less explanation than the math
    • No real deep learning section in the syllabus, and nothing practical after transformers
    • True beginners report feeling lost in the statistics and hyperplane material
Artificial Intelligence & Machine Learning for Business
provider

11

Artificial Intelligence & Machine Learning for Business (2025)

4.5
The Ultimate Artificial Intelligence & Machine Learning course for CxOs, Managers, Team Leaders and Entrepreneurs

iconWhat You'll Learn

  • Applications of Artificial Intelligence and Machine Learning for Business Leaders (CxOs, Managers, Team Leaders, MBA Students, Entrepreneurs)
  • How can you apply Artificial Intelligence and Machine Learning in your areas of functions?
  • Disruption happening in several domains and industries because of Artificial Intelligence and Machine learning

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By Michael Kuhlman on 2020-09-27

Testing our first review, but I do think that we've outdone ourselves on this page. Would love to hear any suggestions or your feedback though!