Best Artificial Intelligence learning resources online: Definition from Digimagg in 2024

The AI industry is booming, growing at 35.6% annually from 2021 to 2026. As demand for AI experts rises, finding the right learning materials can be tough. We've curated a list of free online courses and YouTube channels tailored to different learner backgrounds. This guide aims to help learners choose resources that meet their specific needs in the rapidly evolving AI landscape.

Online Courses

AI for everyone - Coursera

Coursera's "AI for Everyone" course is tailored for those aiming to grasp AI concepts without intricate technicalities, especially for leveraging AI in organizational settings or leading AI projects with non-technical teams. Led by Professor Andrew Ng, a prominent figure in AI and former Chief Scientist at Baidu, the course covers AI project workflows and strategies for business AI deployment.

Introduction to Artificial Intelligence - Udacity

This course is an excellent starting point for learning the basics of statistics and logic in AI, along with their practical applications in computer vision, natural language processing, and robotics. It's an online adaptation of Stanford's CS211 Introduction to Artificial Intelligence, led by renowned AI researchers Sebastian Thrun and Peter Norvig. The course typically spans about four months for completion.

Elements of AI

The Elements of AI course is perfect for those seeking a more basic understanding of AI without delving into complex mathematics or statistics, especially if they lack a computer science background. It focuses on explaining AI's functions, its societal impacts, and how to develop AI systems. Initially created for Finland's AI education initiative, it's now open globally, attracting 730,000+ students from 170 countries.

Learning from data - Caltech (EdX)

This course is a fantastic resource for developing a mathematical comprehension of machine learning theory, encompassing fundamental concepts like probability, matrices, and calculus. Tailored for aspiring data scientists or analysts, it spans 10 weeks and is led by Abu-Mostafa, a professor at Caltech and co-author of the bestselling machine learning book "Learning From Data" on Amazon.

Stanford Machine Learning – Coursera

Andrew Ng's "Machine Learning" course is tailored for learners with programming experience and a foundation in linear algebra. With over 4 million enrollees globally, it enjoys high ratings from students and professionals alike. The course delves into essential machine learning concepts such as supervised learning, unsupervised learning, support vector machines, kernels, and neural networks. It offers hands-on experience through well-crafted exercises drawn from real-world case studies.

Youtube channels

Artificial Intelligence – All in One

This channel is a one-stop destination for AI courses covering crucial topics such as machine learning, neural networks, and natural language processing. Renowned AI experts like Geoffery Hinton, Andrew Ng, and Dan Jurafsky teach these courses, making it a must-visit for AI enthusiasts.

fastai

If you're interested in mastering the construction of deep learning models using the fastai library, created by Jeremy Howard himself, this channel is a must-visit for you.

Yannic Kilcher

This channel is a must-visit for anyone seeking a comprehensive understanding of the latest research articles on deep learning, natural language processing, and reinforcement learning.

Kaggle

This channel is a valuable resource for learning how to apply AI to solve data science problems, offering tutorials on coding deep learning, conducting data processing operations, and creating dashboards.

Two Minute Paper

Stay current with the latest advancements in machine learning through this channel. You'll receive condensed summaries of key ideas and findings from relevant research articles in concise two-minute videos.

Lex Fridman

This channel is perfect for those who enjoy watching interviews with AI industry superstars discussing their work and sharing insights into the future of AI.