7 Best Free Courses for Machine Learning, Artificial Intelligence, and Deep Learning

If you are thinking of learning Data Science, Machine learning (ML), or Deep Learning (DL), you are not alone; More and more people are starting with these advanced skills worldwide.

I have seen a lot of interest from software engineers in the ML and AI space. They are totally caught up with the craze of developing programs that can recognize numbers, alphabets, vehicles, and several other image scanning stuff.

The craze is very similar to what the 1980’s programmer has about video games, where moving a character on screen gives the joy you get when your program correctly identifies the number or letter you make from hand.

From college graduates to junior programmers and from experienced programmers to software architects, all show interest in ML and AI to become part of the next technical revolution we may be witnessing.

If you are wondering what Machine learning and Deep Learning are, let me briefly overview them.

Machine learning programs use algorithms to parse data, learn from that data, and make informed decisions based on what it has learned. One example of that was selecting the best Cucumber from a lot done by a Japanese programmer; you can read the full story here.

On the other hand, deep learning structures algorithms in layers to create an “artificial neural network” that can learn and make intelligent decisions independently. It’s more complicated than ML.

While these free online courses are great, I also recommend you to check out Machine Learning AZ: Hands-On Python and R, if you need a comprehensive, in-depth course on ML. This 45-hour course is fantastic, and you can buy in just $10 on Udemy sales.

image_credit - introduction to deep learning coursera

Image Credit – Coursera

7 Best Free Machine Learning and Deep Learning Courses for Beginners

Before I share the list of courses, I’d like to clarify that they are not of inferior quality even though these courses are free. They are just made free by their instructor for promotional and education purposes.

These courses are taken from popular online learning websites and platforms like Udemy, Pluralsight, Coursera, and FreeCodecamp. Some of them are also available for free on YouTube.

In fact, sometimes these free courses are covered in paid courses once the instructor reaches their promotional targets, so please be careful and check the course price before you join.

Anyway, here is my list of some of the best free online courses to learn Machine Learning and Deep Learning online by yourself.

1. What Is Machine Learning?

This is an excellent free course to learn essential Machine Learning concepts like Supervised, Unsupervised, and Reinforcement Learning with Python demo.

If you are new to Machine Learning, then this free Udemy course is perfect to start with. You will learn about the process of building supervised predictive models and make several of them using Python, the most widely used programming language for machine learning.

As part of the course, you’ll receive the thoroughly annotated Jupyter Notebook used in the course. The best thing about this course is that concepts are presented with lots of examples, animations, and plots, making learning really easy, particularly for beginners.

I highly recommend this course to anyone who wants to learn Machine Learning from scratch. This is good for beginners and even for people with some experience who want to revise the essential machine learning concepts.

2. Practical Machine Learning With Scikit-Learn

Scikit is one of the popular Python Machine learning libraries. It was initially developed by David Cournapeau as a Google Summer of Code project in 2007, and since then, it has become the defacto machine learning library for many programmers.

Scikit-Learn, also known as a skeleton, is particularly great for beginners. It offers a high-level interface for many tasks, allowing beginners to practice the entire machine learning workflow and understand the big picture better.

Anyway, in this course, you’ll not only learn machine learning basics like what is a target variable or a feature but also, you’ll learn how to create an end-to-end model using Python’s SciKit Learn.

Here are key things you will learn in this course:

1. How to implement regression, classification, and boosting algorithms

2. Which algorithms work best for a given dataset

3. Data preprocessing

You’ll get complete hands-on experience with the process of machine learning, which includes importing data, cleaning the data, training, and testing, pre-processing, and feature engineering.

In short, a perfect course for beginners to kick-start their machine learning journey. Once you know Sci-kit, you can explore more powerful libraries like TensorFlow on your own.

3. Deep Learning Prerequisites: The Numpy Stack in Python V2

This is another excellent free course to learn Deep Learning on Udemy. This covers four major Python libraries, like the Numpy, Scipy, Pandas, and Matplotlib stack, crucial to deep learning, machine learning, and artificial intelligence.

If you don’t know, Numpy provides essential building blocks, like vectors, matrices, and operations on them, while Scipy uses those general building blocks to do specific things.

Panda’s strength lies in loading data, particularly from the database. At the same time, Matplotlib helps in looking at that data using some standard plots like the line chart, scatter plot, and histogram.

In this 1.9 hours long course, you will learn all these libraries and learn how to supervise machine learning (classification and regression) with real-world examples using Scikit-Learn.

Here are the main concepts covered in this course:

  1. Basic operations in Numpy, Scipy, Pandas, and Matplotlib
  2. Vector, Matrix, and Tensor manipulation
  3. Visualizing data
  4. Reading, writing, and manipulating DataFrames

You will also learn how to use Numpy, Scipy, Matplotlib, and Pandas to implement numerical algorithms. Most importantly, you will learn the pros and cons of various machine learning models, including Deep Learning Decision Trees, Random Forest, Linear Regression, Boosting, etc.

In short, an excellent free course to learn Deep Learning using Numpy, Scipy, Pandas, and Matplotlib stack.

4. Machine Learning Course for Beginners [FreeCodecamp]

This is another free online course to learn about Machine Learning concepts and it’s available for free on Youtube at freecodecamp’s youtube channel.

This is a comprehensive 9 hour-long Youtube course that is very similar to paid courses like Machine Learning AZ: Hands-On Python and R.

This course will teach you the theory and practical application of machine learning concepts from scratch. This course is developed by Ayush Singh, a 15-year-old kid but you will admire his teaching skill and depth of knowledge.

You can watch this course right here or on youtube:

5. Learn Keras: Build 4 Deep Learning Applications

This is an excellent free Udemy course to learn another powerful Python machine learning library called Keras. If you don’t know, Keras is both a powerful and easy-to-use Python library for developing and evaluating deep learning models.

It wraps the efficient numerical computation libraries like Theano and TensorFlow. It allows you to define and train neural network models in a few short lines of code, which is just awesome.

This free deep learning course will learn how to build an end-to-end Python machine learning project using Keras and tune a deep learning model and neural network.

The best part of this free online course is that the instructor walks through every line of code so you’ll be able to understand the model and the process.

6. How To Think About Machine Learning Algorithms

If you don’t know the question, you probably won’t get the answer right, and this course is all about asking the right machine learning questions.

Machine learning is behind one of the coolest technological innovations today, but contrary to popular perception, you don’t need to be a math genius to successfully apply machine learning.

At first, you need to identify whether machine learning can provide an appropriate solution, and in this course, you’ll learn how to identify those situations. The topics covered in this course include Classifying Data, Predicting relationships using regression, Recommending a product, and Clustering large data sets into meaningful groups.

You need a Pluralsight membership to access this course, which costs around $29 per month. On the other note, Pluralsight is a great resource, and its membership is definitely worth every penny spent. I have bought the annual membership, which comes with a discount. Anyway, even if you don’t have Pluralsight membership, you can still access this course for free by signing up for a 10-day free trial without any commitment, which provides 200 minutes of watch time.

Overall an excellent course to get a high-level overview of what machine learning is and how to use it to solve real-world problems. This is one of the basic machine learning courses, but I have put that to the end because it’s not entirely free.

7. Deep Learning Crash Course for Beginners [FreeCodecamp]

This is a free video course on Youtube to learn Deep Learning in 1 and half hours. This deep learning crash course for beginners is taught by Jason Dsouza and it’s available for free on Freecodecamp’s Youtube channel.

In this free deep learning course, you will learn the fundamental concepts and terminology of Deep Learning, a sub-branch of ML.

This course is designed for absolute beginners with no experience in programming. You will learn the key ideas behind deep learning without any code.

You’ll also learn about neural networks, ML constructs like supervised, unsupervised, and reinforcement learning, the various types of neural network architectures, and more.

You can watch the full video here or on Youtube, it’s free:

That’s all about some of the best free courses to learn ML, AI, DL. As I have said, these are new technologies which will rule the world in the coming years, hence learning them now will provide you with valuable experience and you will be well ahead of others.

At the moment, an ML specialist is also drawing a very handsome salary and solving some interesting world problems. Hence, it’s not only financially rewarding but also works is really great.

Thanks for reading this article so far. If you like these best free DL and ML courses, please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.

PS – If you are looking for the best ML course and don’t mind paying some money, then Machine Learning AZ: Hands-On Python and R is the perfect course to start with. This would be the right choice to learn ML from scratch.

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