25 Best + Free Machine Learning Courses & Certificates [2021]
As featured on Harvard EDU, Stackify and Inc - CourseDuck identifies and rates the Best Machine Learning Courses, Tutorials, Providers and Certifications, based on 12,000+ student reviews, public mentions, recommendations, ratings and polling 5,000+ highly active StackOverFlow members. Learn more
💻 Which Machine Learning Course Provider is best for me?
- 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.
💼 What is Machine Learning used for?
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.
📃 Is a Machine Learning Certificate worth it?
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.
- 1. Machine Learning by Stanford [Coursera] - Best Course Overall
- 2. Machine Learning A-Z: Hands-On Python & R In Data Science [Udemy] - Best Paid Course
- 3. Machine Learning with Python by Sentdex [YouTube] - Best YouTube Tutorial
- 4. Python for Data Science and Machine Learning Bootcamp [Udemy] - Editor's Choice
- 5. Practical Deep Learning for Coders, v3 [fast.ai] - Best Practical Course
- 6. Learn Machine Learning By Building Projects [Eduonix] - Best NEW Course
- 7. Neural Networks and Deep Learning [Coursera] - Best Advanced Course
- 8. Google's Machine Learning Crash Course [Google Developers] - Best Short Course
- 9. Machine Learning [Udacity]
- 10. MIT Deep Learning for Self-Driving Cars [YouTube]
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399 Filtered Courses
Best Course Overall
1 )
Machine Learning by Stanford (2011)
4.8
Created by the co-founder of Coursera, this course will provide you with a broad introduction to Machine Learning. It is the #1 highest rated Machine Learning course on Coursera and an excellent choice for beginners with no programming experience.
Pros
Cons
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- Highly recommended as your first course to dive into Machine Learning.
- Although it requires hard work, the course is very accessible for beginners.
- Presented by an expert in the field of Machine Learning and online teaching.
- Well designed with simple explanations and comprehensive content.
- Focused on the logic behind Machine Learning rather than programming and maths.
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- Experienced developers may consider lectures and assignments to be too basic.
- Taught in Matlab/Octave, not Python.
- Lacks practical examples.
Best Paid Course
2 )
Machine Learning A-Z: Hands-On Python & R In Data Science (2022)
4.5
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
What You'll Learn
- Master Machine Learning on Python & R
- Have a great intuition of many Machine Learning models
- Make accurate predictions
- Make powerful analysis
- Make robust Machine Learning models
- Create strong added value to your business
- Use Machine Learning for personal purpose
- Handle specific topics like Reinforcement Learning, NLP and Deep Learning
- Handle advanced techniques like Dimensionality Reduction
- Know which Machine Learning model to choose for each type of problem
- Build an army of powerful Machine Learning models and know how to combine them to solve any problem
Best YouTube Tutorial
3 )
Machine Learning with Python by Sentdex (2016)
4.6
Comprehensive Machine Learning series covering everything from linear regression to neural networks provided by a famous YouTube instructor, Sentdex. This tutorial features 72 videos, and it's ideal for learners that have a basic understanding of Python.
Pros
Cons
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- In-depth tutorial covering many major topics of Machine Learning.
- Great for beginners as well as intermediate level learners.
- Interesting and knowledgeable instructor with practical approach to learning.
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- Requires foundational knowledge in data science and Python.
Editor's Choice
4 )
Python for Data Science and Machine Learning Bootcamp (2022)
4.5
Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!
What You'll Learn
- Use Python for Data Science and Machine Learning
- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy for Numerical Data
- Learn to use Pandas for Data Analysis
- Learn to use Matplotlib for Python Plotting
- Learn to use Seaborn for statistical plots
- Use Plotly for interactive dynamic visualizations
- Use SciKit-Learn for Machine Learning Tasks
- K-Means Clustering
- Logistic Regression
- Linear Regression
- Random Forest and Decision Trees
- Natural Language Processing and Spam Filters
- Neural Networks
- Support Vector Machines
Best Practical Course
5 )
Practical Deep Learning for Coders, v3 (2019)
4.3
Text-based and video-based introductory Machine Learning course taught by an experienced instructor and Kaggle's #1 competitor. Using PyTorch and fastai library, this tutorial is focused on practical results rather than theory.
Pros
Cons
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- Experienced instructor that provides easy to understand explanations and teaches you "how-to" instead of "why".
- Top-down learning approach perfect for students that want to apply Machine Learning fast.
- Great community of fellow-learners to help you along the course.
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- This course uses fastai library that can be too difficult for beginners.
- To understand the theory befind the course, further readings and additional information are necessary.
Best NEW Course
6 )
Learn Machine Learning By Building Projects (2022)
0.0
Learn to build real world machine learning solutions across different verticals. Master professional machine learning.
What You'll Learn
- Machine learning
- Python
- Learn core concepts of Machine Learning
- Learn about differnt types of machine learning algorithms
- Build real world projects using Supervised and Unsupervised learning algorithms
- Learn to implement neural networks
Best Advanced Course
7 )
Neural Networks and Deep Learning (2017)
4.7
Learn how to build and implement your own deep neural networks in just 7 hours. Taught by an experienced instructor, this is the first course in the Deep Learning Specialization.
Pros
Cons
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- Offered by deeplearning.ai, a well known provider of a world-class AI education.
- Taught in Python and Jupyter Notebook.
- Good introduction to how to build and implement neural networks.
- Easy to understand lectures with a mix of theory and practical application.
- Useful tips and insights into Deep Learning.
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- Pre-written code in assignments.
- Repetitive content.
Best Short Course
8 )
Google's Machine Learning Crash Course (2018)
3.8
Taught by Google experts, this free, concise, and highly interactive course will give you a basic understanding of Machine Learning concepts. Learn and practice at your own pace, using TensorFlow APIs.
Pros
Cons
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- The course is taught by Google engineers and researchers, experts in the field of Machine Learning.
- Short and sweet course but with relevant curriculum for complete beginners.
- Interactive quizzes, programming and playground exercises.
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- The only framework for building ML models presented in the course is TensorFlow.
- Vague explanations of Machine Learning concepts make some of the exercises too difficult for students.
9 )
Machine Learning (2015)
4.7
Learn Supervised, Unsupervised and Reinforcement Learning approaches from entertaining and competent instructors. Offered at Georgia Tech, this free and interactive course covers an interesting area of Artificial Intelligence.
Pros
Cons
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- The course is a part of the Online Masters Degree at one of the best universities for computer science.
- Charming and entertaining instructors.
- Broad survey of the Machine Learning field.
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- Unique style of teaching that will not suit everyone.
- Long and Time-consuming.
10 )
MIT Deep Learning for Self-Driving Cars (2019)
4.1
Learn Deep Learning from a research scientist at MIT, one the world's most reputable universities. Great collection of courses and lectures, providing informative content and real-world examples.
Pros
Cons
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- The instructor is a researcher from one of the most prestigious universities in the world.
- The concepts are presented in a clear and straight-forward manner.
- Real-world examples to help you understand how to apply the theory behind Deep Learning.
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- Too many topics covered in one tutorial, only scratches the surface of each.
- Lacks interactivity which can be inconvenient for learners to easily comprehend key concepts.
11 )
Machine Learning with Python by IBM (2018)
4.7
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed!
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Overall Score : 96 / 100