A basic grounding in the principles and practices around artificial intelligence (AI), automation and cognitive systems is something which is likely to become increasingly valuable, regardless of your field of business, expertise or profession. Here are the top 6 articial intelligence courses that are available free of cost.
Today you learn all these technologies without taking admission in university. A growing number of online courses have sprung up in recent years covering everything from the basics to advanced implementation.
In this post I will give a rundown of some of the best free ones which are available today.
Learn and apply fundamental machine learning concepts with the Crash Course. And get real-world experience with the companion Kaggle competition.
visit Learn with Google AI to explore the full library of training resources.
It is slightly more in-depth course from Google offered through Udacity. As such, it isn’t aimed at complete novices and assumes some previous experience of machine learning, to the point where you are at least familiar with supervised learning methods.
It focuses on deep learning, and the design of self-teaching systems that can learn from large, complex datasets.
2. Learn With Google AI:
Newly launched resource is part of Google’s plan to broaden the understanding of AI among the general public. Material is slowly being added but it already contains a Machine Learning with TensorFlow crash course.
In this course you’ll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
3. Stanford University – Machine Learning:
This course is absolutely free of cost. But you may go for the paid certification if you want to make career in machine learning.
4. Columbia University – Machine Learning:
This course is also available in its entirety for free online, with an option to pay for certification should you need it.
It promises to teach models, methods and applications for solving real-world problems using probabilistic and non-probabilistic methods as well as supervised and unsupervised learning.
It is offered through the non-profit edX online course provider, where it forms part of the Artificial Intelligence nanodegree.
5. Nvidia – Fundamentals of Deep Learning for Computer Vision:
Computer vision is the AI sub-discipline of building computers which can “see” by processing visual information in the same way our brains do.
As well as the technical fundamentals, it covers how to identify situations or problems which can benefit from the application of machines capable of object recognition and image classification.
The final assessment covers building and deploying a neural net application, and while the entire course can be studied at your own pace, you should expect to spend around eight hours on the material.
6. MIT – Deep Learning for Self Driving Cars:
As with the course above, MIT takes the approach of using one major real-world aspect of AI as a jumping-off point to explore the specific technologies involved.
The self-driving cars which are widely expected to become a part of our everyday lives rely on AI to make sense of all of the data hitting the vehicle’s array of sensors and safely navigate the roads. This involves teaching machines to take data from sensors.
Google givemoney to universities to increase imapct of artificial intelligence in researches: