Almost everyone learning AI right now is learning it on top of NVIDIA hardware whether they realise it or not, so going straight to the source for training has an obvious logic to it, and the Deep Learning Institute is that source. The thing that genuinely sets it apart from the endless sea of online courses is that the labs do not run in some simplified sandbox, they run on real GPU-accelerated cloud instances that NVIDIA spins up for you, which means when you train a model you are doing it on the kind of kit the work is really done on, and that practical grounding is hard to get anywhere else without paying for your own cloud time. The teaching itself is exactly what you would hope for from an engineering company, dense, practical and completely free of the motivational padding that bloats so many courses. The catalogue spans deep learning fundamentals, generative AI and large language models, accelerated computing with CUDA, and data science, and on selected courses you can sit an exam and earn a certificate that carries real credibility with technical hiring managers precisely because of whose name is on it.
I also appreciate the honest pricing spread. A good number of the self-paced courses are free, which lets you test the waters at no cost, and the paid courses and workshops are reasonably priced until you reach the full-day instructor-led sessions, which is where the cost climbs. Now the caveats, and they are real. This is NVIDIA's training, so it lives inside NVIDIA's ecosystem, CUDA and the surrounding stack, and while that is the dominant ecosystem in practice, you should know going in that this is not a neutral tour of the field.
It also assumes you arrive with genuine prerequisites, comfort with Python and some grasp of machine learning concepts depending on the course, so it is emphatically not where a complete beginner should begin, you would drown. The other friction is organisational rather than educational, the catalogue is sprawling and not laid out as one obvious path, so you have to do some work yourself to assemble a sensible sequence rather than being walked through a curriculum. My recommendation is to treat the free self-paced courses as your audition. Pick one in the area you care about, see whether the level and pace fit you, and if they do, spend money on the workshop that takes you deep into the specific topic you need, because the combination of real GPU practice and a credible certificate is a genuinely strong package for someone who is already technical and wants to get serious.