Today, we are going to look at some of the best online courses to learn Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning (DL). These online classes are targeted towards developers of varying abilities – from student and novice programmers to seasoned coders looking to add additional software development concepts to their repertoire. The languages used in these courses will vary, but the majority will rely on an understanding of either Python or R – both of which excel in the Machine Learning and data science arenas.
If the courses listed in this tutorial are not what you are looking for, you can also check out Coursera’s Data Science and Machine Learning courses listing page, which also features degree and certification programs for data analysts and data scientists.
Machine Learning Online Courses
Below are some of the best online courses to learn Machine Learning principles, ranked in no particular order.
Machine Learning Specialization from Udemy
The Machine Learning Specialization course from Udemy is a great place to start if you are looking to get a deep understanding of Machine Learning principles and concepts, all with code examples, code quizzes, and hands-on examples. The specialization comprises three courses, and, by the end of the classes, students will earn a certificate of completion.
The first part of this ML course focuses on supervised machine learning, which includes topics like regression and classification. What that means is that students will learn how to build machine learning models using the Python programming language and, in particular, the powerful and well-known Numpy and sckit-learn libraries.
Part two discusses advanced learning algorithms. Pupils will not only build a neural network with TensorFlow, but also train it, teaching it how to perform multi-class classifications.
For the final part, unsupervised learning, recommenders, and reinforcement learning are all covered. Learning techniques, including clustering and anomaly detection wrap up thie specialization.
For more information or to sign-up for the Machine Learning course, check out its listing on Udemy: Machine Learning Specialization.
Deep Learning Specialization from Udemy
Another Machine Learning specialization course offered by Udemy, Deep Learning Specialization, also features three distinct sets of curriculum, all centered around teaching students how to work with deep neural networks. It is considered an intermediate level course, and pupils are expected to have an understanding of such programming concepts as loops, if and else statements, and data structures as a basic requirement to take the class. Basic linear algebra and machine learning knowledge are also required.
There are some unique elements to this online Deep Learning course that really caught our eye. For starters, during this course students will build a Convolutional Neural Network (CNN) and set it about the task of detecting and recognizing tasks. That same CNN will be used to generate art via neural style transfer, and apply algorithms to image and video data.
By the end of the course you will be able to use Python and TensorFlow to develop a system that can synthesize music, recognize speech, perform natural language processing, and launch chatbots.
You can learn more about the different areas of Deep Learning and Artificial Intelligence this online course covers by visiting its page on Udemy: Deep Learning Specialization.
AI For Everyone from Udemy
The AI For Everyone course, also from Udemy, makes our list for several reasons. For starters, it is a beginner level course with no prerequisites. Second the course is only 12 hours long and serves as a great introduction to concepts associated with Machine Learning, meaning, if you have no prior experience, this course will get you up to speed so you can begin taking some of the other Machine Learning classes on our list.
Students taking the AI For Everyone course will learn the following:
- Common AI terminology, such as definitions for neural networks, machine learning, deep learning, and data science.
- A realistic view of what Artificial Intelligence is truly capable of, and, perhaps more importantly, what it cannot do.
- How to use AI to solve problems in a business or organizational environment.
- How to build Machine Learning and Data Science applications and projects
- How to navigate working with an AI team and build a foundational AI strategy.
- The ethical and societal implications of artificial intelligence and what they mean for society going forward.
- Business elements of AI and how Artificial Intelligence, Deep Learning, and Machine Learning apply to the business world.
You can sign up for this online AI course by visiting its Udemy listing: AI For Everyone.
Facial Expression Recognition with Keras from Udemy
If you have read any of my previous course highlight articles, you know that I love courses that serve a specific, real-world applicable purpose. The Facial Expression Recognition with Keras class is just such an offering. Offered by Udemy, this Machine Learning course is only two hours long, but still manages to pack in a lot of information. It is an intermediate level guided project that starts by teaching students how to build and train a Convolutional Neural Network using Keras.
Using a provided data set, pupils will use the CNN to recognize facial expressions from one of seven categories, such as angry, disgust, and happy. Once the emotion is “recognized” bounding boxes will be drawn around the faces to help in facial detection. After adequately training your neural network, you can then launch a web interface and conduct real-time facial expression recognition and analysis based off of user provided video and images.
If you want to sign-up for this course, you can do so by visiting its page on Udemy: Facial Expression Recognition with Keras.
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