Fellowship.AI Reviews

4.1

86% would recommend to a friend

(32 total reviews)
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Arshak Navruzyan

84% approve of CEO

71% positive business outlook

Fellowship.AI has an employee rating of 4.1 out of 5 stars, based on 32 company reviews on Glassdoor which indicates that most employees have an excellent working experience there. The Fellowship.AI employee rating is in line with the average (within 1 standard deviation) for employers within the Education industry (3.7 stars).

Reviews by job title

32 reviews
5.0
3 Jul 2025

Fellowship review

Recommend
CEO approval
Business outlook

Pros

Great place to get exposed to state of the art AI and real world challenges/projects in AI/Datascience/ML.

Cons

No such Cons and problems

1.0
5 Dec 2019

WASTE of TIME and MONEY

Recommend
CEO approval
Business outlook

Pros

There are absolutely no advantages to the internship at Fellowship.AI

Cons

As I am currently on the Fellowship program (Sep - Dec 2019), I am able to share my experience from within Fellowship.AI. What I am about to share is not only my personal view but resonates with quite a few fellows who I was able to talk to via the Slack (which is the communication platform used by Fellowship.AI). If you decide to apply for the Fellowship program be aware that you are not going to learn anything useful about data science, machine learning or deep learning. There will not be any mentors who you will be able to learn from. You will not get any support from Fellowship.AI on your path to becomming a data scientist. You will get the opportunity to waste your time for a period of 4 months. You will have to devote the majority of your time to donwloading images from Google Images which Fellowship.AI is going to use for their own commercial purposes. Even more time you will have to devote to cleaning the image datatset. You are not going to apply any state-of-the-art deep learning methods. The best what you can hope for is training a resnet34 architecture using the fastai library (which provides a ready-to-use implementation of the resenet34 architecture) on the images you have downloaded. At the very start of the program there was a presentation by Arshak (CEO of Fellowship.AI) to fellows in which he talked about an exclusive machine learning community, about how much we are going to learn about machine learning and that we should be very grateful for having been accepted to the program. He advised us to think about how we could give back to Fellowship.AI. To me it was clear after the first month that there is no machine learning community. The only thing that is there is the commercial platform Platform.AI which exploites the fellows as free labour.

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Fellowship.AI Response
5y
Mentorship is provided by our program. All the work of the fellows is reviewed regularly and feedback is provided along with guidance. We try to provide the fellows with real-world working environment as much as possible instead of spoon-feeding them. We give them leeway to be creative with their solutions because in real-world, no one is going to point you to the correct direction, rather you need to find solutions yourself which we believe is really important and aspire to provide our fellows as much as possible. Data collection, curation is a major part of being a data scientist and it is not for everybody. You need to come up with ways to solve a problem even when you are not given a clean dataset as on kaggle competition. You do work on SOTA architectures and it isn't just limited to the fastai library. The more you give to the program, the more you get in return. This experience is invaluable and we leave it in your hands, how you use this chance, to either show your skills and get a jump start, or to just waste your time doing nothing.
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Glassdoor has 88 Fellowship.AI reviews submitted anonymously by Fellowship.AI employees. Read employee reviews and ratings on Glassdoor to decide if Fellowship.AI is right for you.