GeeksforGeeks earned its reputation as a reference, and that is still where its real value sits. For well over a decade it has been one of the first results people land on when they search for how a sorting algorithm works, how to do something specific in Python, or what the intuition behind a machine learning method is, and its library of articles on data structures, algorithms, machine learning and data science is genuinely vast. When you already know roughly what you are looking for, this is a fantastic resource, because the pages tend to lead with a clear explanation and a small runnable code example, which is exactly what you want when you are mid task and need to remember how something works or check the shape of an implementation. For a student revising for exams or a working developer filling a specific gap, the free content is hard to beat on breadth and convenience.
The company has since expanded well beyond articles into paid products, including self paced courses and live online programmes covering data science, machine learning and AI, usually priced for the Indian market that makes up much of its audience. This is where I would temper expectations. The strength of GeeksforGeeks was never a single authored, carefully sequenced curriculum, it was a huge crowd built encyclopedia, and that heritage shows in the courses, which can feel more like structured collections of the kind of material the site already does for free than a purpose built learning experience with the polish of a dedicated course provider. Because so much of the underlying content is community contributed, quality and depth also vary from one topic to the next, and you cannot assume every page or module carries the same rigour.
The free site is also increasingly hard to read comfortably, with dense advertising wrapped around the content, which is the trade for it being free but does wear on you during a long study session. The deeper limitation is a conceptual one. Reference material is brilliant for answering a specific question, but learning a field like machine learning well needs connected understanding built across projects, and a site optimised for individual lookup pages is not naturally set up to deliver that joined up progression, so even the paid courses tend to be stronger on explaining pieces than on making them cohere. My take is to use GeeksforGeeks for exactly what it is best at, which is a free, always open reference and revision companion that belongs in your bookmarks and will save you time constantly.
Before buying one of its structured or live courses, though, weigh it honestly against providers whose whole product is a designed learning journey, because paying for a course from a site whose genius is reference is not automatically the best way to spend your money.