augmented intelligence certification (AI),</a> automation and cognitive systems is something which is likely to become increasingly valuable, regardless of your field of business, expertise or profession.</p> ;<div id="attachment_2704" class="wp-caption alignnone"> ; <div class="article-body-image"> ; <progressive-image class="size-large wp-image-2704" src="https://blogs-images.forbes.com/bernardmarr/files/2018/04/AdobeStock_144004104-1200×814.jpg" alt="" data-height="814" data-width="1200"></progressive-image> ; </div> ; <div article-image-caption=""> ; <div class="caption-container" ng-class="caption_state"> ; <p class="wp-caption-text">Adobe Stock<small class="article-photo-credit">Adobe Stock</small></p> ; </div> ; </div> ;</div> ;<p>Fortunately, today you don’t have to take years out of your life studying at university to become familiar with this seemingly hugely complex technology. A growing number of online courses have sprung up in recent years covering everything from the basics to advanced implementation.</p> ;<p>Some are aimed at people who want to dive straight into coding their own artificial neural networks, and understandably assume a certain level of technical ability. Others are useful for those who want to learn how this technology can be applied by anyone, regardless of prior technical expertise, to solving real-word problems.</p> ;<p> ; </p> ;<p>In this post I will give a rundown of some of the best free ones which are available today.</p> ;<p><a href="https://ai.google/education/" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://ai.google/education/">Learn with Google AI</a></p> ;<p>This 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 (Google’s machine learning library) crash course.</p> ;<div class="vestpocket" vest-pocket=""></div> ;<p>The course covers the ground from a basic introduction to machine learning, to getting started with TensorFlow, to designing and training neural nets.</p> ;<p>It is designed so that those with no prior knowledge of machine learning can jump in right at the start, those with some experience can pick or choose modules which interest them, while machine learning experts can use it as an introduction to TensorFlow.</p> ;<p><a href="https://www.class-central.com/course/udacity-deep-learning-5681" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.class-central.com/course/udacity-deep-learning-5681">Google – Machine Learning</a></p> ;<p>This is a 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.</p> ;<p>It focuses on deep learning, and the design of self-teaching systems that can learn from large, complex datasets.</p> ;<p>The course is aimed at those looking to put machine learning, neural network technology to work as data analysts, data scientists or machine learning engineers as well as enterprising individuals wanting to make use of the plethora of open source libraries and materials available.</p> ;<p><a href="https://www.coursera.org/learn/machine-learning" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.coursera.org/learn/machine-learning">Stanford University – Machine Learning</a></p> ;<p>This course is offered through Coursera and is taught by Andrew Ng, the founder of Google’s deep learning research unit, Google Brain, and head of AI for Baidu.</p> ;<p>The entire course can be studied for free, although there is also the option of paying for certification which could certainly be useful if you plan to use your understanding of AI to increase your career prospects.</p> ;<p>The course covers the spectrum of real-world machine learning implementations from speech recognition and enhancing web search, while going into technical depth with statistics topics such as linear regression, the backpropagation methods through which neural networks “learn”, and a Matlab tutorial – one of the most widely used programming languages for probability-based AI tools.</p> ;<p><a href="https://www.class-central.com/course/edx-machine-learning-7231" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.class-central.com/course/edx-machine-learning-7231">Columbia University – Machine Learning</a></p> ;<p>This course is also available in its entirety for free online, with an option to pay for certification should you need it.</p> ;<p>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.</p> ;<p>To get the most out of the course you should expect to spend around eight to ten hours a week on the materials and exercises, over 12 weeks – but this is a free Ivy League-level education so you wouldn’t expect it to be a breeze.</p> ;<p>It is offered through the non-profit edX online course provider, where it forms part of the augmented intelligence certification nanodegree.</p> ;<p><a href="https://www.class-central.com/course/fundamentals-of-deep-learning-for-computer-vision-10730" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.class-central.com/course/fundamentals-of-deep-learning-for-computer-vision-10730">Nvidia – Fundamentals of Deep Learning for Computer Vision</a></p> ;<p>Computer vision is the AI sub-discipline of building computers which can “see” by processing visual information in the same way our brains do.</p> ;<p>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.</p> ;<p>As a manufacturer of graphics processing units (GPUs), Nvidia unsurprisingly covers the crucial part these high-powered graphical engines, previously primarily aimed at displaying leading-edge images, has played in the widespread emergence of computer vision applications.</p> ;<p>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.</p> ;<p><a href="https://selfdrivingcars.mit.edu/" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://selfdrivingcars.mit.edu/">MIT – Deep Learning for Self Driving Cars</a></p> ;<p>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.</p> ;<p>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 interpret data from those sensors just as our own brains interpret signals from our eyes, ears and touch.</p> ;<p>It covers the use of the MIT DeepTraffic simulator, which challenges students to teach a simulated car to drive as fast as possible along a busy road without colliding with other road users.</p> ;<p>This is a course taught at the bricks ‘n’ mortar university for the first time last year, and all of the materials including lecture videos and exercises are available online – however you won’t be able to gain a certification.</p>”>
A simple grounding in the principles and tactics all around augmented intelligence certification (AI), automation and cognitive systems is one thing which is probably to come to be progressively worthwhile, irrespective of your industry of small business, skills or career.
Fortunately, right now you do not have to take many years out of your lifetime researching at college to come to be common with this seemingly hugely advanced technologies. A rising variety of on the web courses have sprung up in modern several years masking almost everything from the fundamental principles to sophisticated implementation.
Some are aimed at men and women who want to dive straight into coding their very own synthetic neural networks, and understandably assume a particular stage of complex means. Some others are helpful for these who want to study how this engineering can be used by any individual, irrespective of prior technological knowledge, to fixing true-phrase issues.
In this post I will give a rundown of some of the best cost-free kinds which are readily available right now.
Find out with Google AI
This recently released useful resource is part of Google’s prepare to broaden the understanding of AI amongst the common general public. Materials is slowly but surely being additional but it by now includes a Machine Learning with TensorFlow (Google’s machine learning library) crash course.
The course covers the ground from a primary introduction to machine learning, to getting started off with TensorFlow, to creating and training neural nets.
It is intended so that these with no prior expertise of machine learning can bounce in proper at the begin, people with some encounter can decide or choose modules which desire them, although machine learning industry experts can use it as an introduction to TensorFlow.
Google – Machine Learning
This is a a little bit extra in-depth course from Google offered via Udacity. As this kind of, it is not aimed at full novices and assumes some prior working experience of machine learning, to the issue where you are at least familiar with supervised understanding methods.
It focuses on deep learning, and the style of self-teaching techniques that can learn from huge, complex datasets.
The course is aimed at those people wanting to put machine learning, neural community technological know-how to do the job as knowledge analysts, facts researchers or machine learning engineers as properly as enterprising persons wanting to make use of the myriad of open up supply libraries and components accessible.
Stanford College – Machine Learning
This course is supplied via Coursera and is taught by Andrew Ng, the founder of Google’s deep learning investigate device, Google Brain, and head of AI for Baidu.
The whole course can be analyzed for absolutely free, though there is also the option of spending for certification which could absolutely be useful if you system to use your comprehension of AI to boost your profession potential clients.
The course addresses the spectrum of serious-globe machine learning implementations from speech recognition and maximizing world wide web look for, while going into technological depth with data subject areas this kind of as linear regression, the backpropagation procedures through which neural networks “learn”, and a Matlab tutorial – a single of the most commonly applied programming languages for chance-centered AI equipment.
Columbia University – Machine Learning
This course is also accessible in its entirety for cost-free on-line, with an possibility to shell out for certification should really you want it.
It promises to teach products, strategies and applications for solving genuine-earth issues making use of probabilistic and non-probabilistic methods as nicely as supervised and unsupervised learning.
To get the most out of the course you should really count on to shell out all-around 8 to ten several hours a 7 days on the components and exercises, around 12 months – but this is a absolutely free Ivy League-level education and learning so you wouldn’t expect it to be a breeze.
It is offered by means of the non-revenue edX online course service provider, the place it kinds part of the augmented intelligence certification nanodegree.
Nvidia – Fundamentals of Deep Learning for Personal computer Eyesight
Personal computer vision is the AI sub-willpower of creating computer systems which can “see” by processing visual info in the exact same way our brains do.
As well as the complex fundamentals, it covers how to discover situations or issues which can reward from the software of equipment able of object recognition and image classification.
As a company of graphics processing units (GPUs), Nvidia unsurprisingly addresses the crucial portion these large-driven graphical engines, previously mostly aimed at displaying primary-edge illustrations or photos, has played in the common emergence of pc eyesight applications.
The ultimate assessment covers creating and deploying a neural net software, and although the complete course can be researched at your personal tempo, you should assume to commit all-around eight hours on the material.
MIT – Deep Learning for Self Driving Autos
As with the course earlier mentioned, MIT can take the tactic of using just one key serious-globe element of AI as a jumping-off point to discover the precise technologies concerned.
The self-driving cars which are…