There has been a silent revolution going on in the world and it’s being brought about by Machine Learning. Instead of teaching computers how to perform intricate tasks, we now apply this Machine Learning to develop intelligent systems that let them learn how to do it themselves. Online learning courses are the perfect starting point if you want to become part of this transformation that’s quietly reshaping the tech industry.
What is Machine Learning?
A branch of Artificial Intelligence (AI), Machine Learning focuses on developing algorithms that can learn from data. This discipline is used to build complex statistical and mathematical networks based on vast quantities of data. Machine learning models are also used in chatbots, spam filtering, ad serving, search engines and fraud detection. It is mostly used in business analytics, health informatics, financial forecasts and self-driving automobiles.
Here are the best online Machine Learning courses for beginners:
Machine Learning for All by University of London — on Coursera
Offered by the University of London, this 22-hour course defines both AI intelligence and machine learning as it explores how these disciplines are related to each other. You do not need advanced mathematical expertise or a good grip on machine learning platforms like Python or TensorFlow for this course. Here you will learn how to collect data, train a model and put it to test in order to complete a machine learning project. After completion of this course, you’ll know the fundamentals of machine learning and its diverse applications.
Machine Learning Crash Course by Google — on Google AI Education
This 15-hour course is part of Google AI Education, which is a free platform that contains articles, videos and interactive content. The course includes the essential concepts that would help you resolve machine learning challenges quickly. Python is the programming language of choice and TensorFlow is introduced in the course. Each major portion of the curriculum has a Google Colab-hosted interactive Jupyter notebook. All the video lectures and articles are brief and to the point — they will help you progress through the course at your own pace.
Machine Learning by Stanford University — on Coursera
This is one of the first online machine learning courses that helped spread the popularity of the discipline. It is taught by the renowned computer scientist Andrew Ng. The mathematical foundations of machine learning are laid out in this 61-hour course. Before moving on to multivariate and logistic regression, it starts with a review of linear algebra and univariate linear regression. Here you will also learn practical issues like how to plan and implement large-scale machine learning initiatives.
Machine Learning A-Z™: Hands-On Python & R In Data Science — on Udemy
This 50-hour course provides a thorough and practical overview of machine learning. It gradually progresses from data preprocessing to model validation, but some of the underlying maths is glossed over. The course begins with a discussion of various regression, classification and clustering models. It covers the principles of artificial neural networks as well as reinforcement learning and natural language processing. Along with Python and R programming languages, the TensorFlow machine learning package is used throughout the course.
Complete Machine Learning & Data Science Bootcamp 2022 — on Udemy
This 45-hour course covers both Python programming and machine learning. After setting up your programming environment, you’ll dive into a Python crash course in the first portion of the course — it will help you master the basics of the programming language as well as a variety of popular libraries like NumPy, Pandas and Matplotlib. You’ll be ready to tackle the second part of the course, which is totally dedicated to machine learning, once you have developed Python programming abilities.
IBM Machine Learning Professional Certificate by IBM — on Coursera
This six-month course offered by IBM teaches machine learning through a hands-on approach using Python, which is deemed as a major AI programming language. You need to brush up your calculus as this course will challenge you with maths skills. Machine learning basics and applications in sectors such as healthcare, banking and telecommunications are covered in the first part of the course. It also discusses the differences between supervised and unsupervised learning.
Machine Learning for Musicians and Artists by Goldsmiths, University of London — on Kadenze
This 56-hour course is the most unconventional on the list as it addresses machine learning from an aesthetic perspective, ranging from music to visual arts. Here you will master the principles of machine learning through the lens of art, motion and music. The course will teach you how to read human movement, music and other real-time input using machine learning.