Data scientists increasingly need higher number and machine learning is integral part of one's training. Online courses have streamlined access to quality education from some of the world's best universities and industry leaders, and this review highlights the best online machine learning courses – focusing on content quality, flexibility, and affordability.
Online learning has become trendy both among professionals and among students, particularly those interested in data science; it has been learned online. As mentioned above, there are numerous reasons why machine learning may be advantageous when studied online; some of them are the following:
Coursera – Machine Learning by Andrew Ng: Among one of the very popular and highly regarded Stanford University online courses on Coursera, this course is certainly taught by one of the co-founders of the field. This is taught by Andrew Ng and includes theories along with practical applications of machine learning, which makes it valuable for both new and experienced professionals. It covers supervised vs. unsupervised learning, neural networks, etc. Over 4.8 million enrollments make it an extremely useful site for intending data scientists. edX – Data Science:
Machine Learning by Harvard University: This is part of the Harvard University Data Science Professional Certificate course in edX. This course covers the fundamentals of machine learning, including key concepts such as linear regression, classification, and algorithms. It follows a programming course in R that is in wide use with respect to data science. It would be ideal for learners who have a background in programming and wish to expand their knowledge of machine learning.
Udacity – Intro to Machine Learning with PyTorch: Udacity offers a more hands-on means of learning, as it does so with projects. This course on machine learning focuses on working with popular PyTorch- a famous machine learning framework- and highlights hands-on experience. The course focuses on supervised and unsupervised learning; the students get the chance to apply all this knowledge toward real-world projects, including building predictive models. In case you are interested in an immersive means of learning that focuses on applying machine learning towards real problems, then this course is an excellent option.
DataCamp – Machine Learning Fundamentals with Python: DataCamp focuses on the usage of machine learning using Python, one of the most popular programming languages in the field. The course introduces you to key machine learning concepts and their application in real scenarios using the mighty libraries in Python that include scikit-learn. It is perfect for beginners entering into the world of data science. With its interactive platform, it ensures that you gain practical experience while you learn.
Google – Machine Learning Crash Course: Google offers a free crash course on machine learning that is just brilliant for anyone looking to obtain a quick introduction to the field. It's great for beginners since it's a compact presentation of practical exercises as well as theoretical knowledge. This course also comprises TensorFlow lessons, Google's own open-source library of machine learning; therefore, it's an excellent starting point for those who would like to dive further into more complex concepts later on.
The key considerations when selecting an online course in machine learning include the following:
Whether you are a beginner or an expert, online courses on machine learning are ideal for learning. From Coursera's Andrew Ng comprehensive class on machine learning to Google's crash course for starters, there is just the right fit for everyone. And as the innovation in the area of data science continues being driven by machine learning, the investment through these online courses is sure to power into an interesting and prosperous career.