Hi everyone! My name is Jeremie Harris, and I’m the co-founder of SharpestMinds, an internship platform that finds students and new grads opportunities in machine learning to kick-start their careers. Companies that post to our platform are explicitly looking for full-time employees, and use the internship stage to get to know promising students and graduates.
I actually got my start with deep learning through Fast.ai’s course 1 back in the day, and I’ve seen how well this course prepares people for the “real world” of ML development.
As a result, we’re offering a special deal to Fast.ai students and alums. We’ll fast-forward Fast.ai students and grads past the resume review phase of our application process, straight to the technical interview and GitHub review steps.
If you’re interested, apply through our website at sharpestminds.com/student/signup. Be sure to enter your name as “[first name] [last name] (Fast.ai)” so that we know to advance you straight to the interview stage. We’ve just launched our beta in the US, so you’d be part of one of our first American batches, and we’d love to get your feedback, so feel free to email me anytime at jeremie@sharpestminds.com.
Thanks @jeremie! FYI I’ve moved this post into #part1-v2 so it gets more visibility.
I spoke with Jeremie about this, and they’ll be contributing to fast.ai’s scholarships based on the success of this project. I told him I was happy just to have a good “graduation” path for our students, but this makes it even better!
To ensure that this opportunity works well for all students, please don’t apply for SharpestMinds until you’ve completed the course and are well enough practiced with the techniques that you can confidently apply them. That is - be sure you can complete the recommended assignments from each lesson! (Remember, SharpestMinds are very good at the interview process, so you’ll be wasting their time and yours if you aren’t ready when you apply.)
Hi Aditya, we’re mainly focused in the US and Canada at the moment (since that’s where our hiring partners are currently located), but we have taken exceptional students from overseas as well in the past. Feel free to apply!
Update: we’ve just finished compiling statistics for the February cohort, and the results were pretty remarkable:
Average acceptance rate for non-Fast.ai applicants: 14.5%
Average acceptance rate for Fast.ai applicants: 67%
This says a lot about how well the course can prepare people for industry in ML (to the extent that our screens are a good proxy for industry readiness of course; and on this note, 75% of our December cohort have landed positions with companies on the platform, so it’s probably not a bad assumption).
Also if you want to apply to our March cohort, you can do so here! --> sharpestminds.com
I am wondering what kind of people you consider hiring.
Quick intro about me: I am a recent graduate in Engineering Geology from a high ranked university with a decent background in data processing and numerical modelling in MATLAB. But with the great advancements and extreme flexibility in ‘big-data’ and machine-learning I would like to start my career as a Data Scientist. I spend a lot of time and improving rapidly in fastai/deep learning and look forward to applying my newly acquired skill to a job. So, I am not a mathematician, statistician or computer scientist and have currently mediocre machine learning skills but I do have a strong scientific background.
So If I continue my machine learning path. Finish the fastai course, have a few decent scores on kaggle, and a decent résumé, would that qualify me as a suitable candidate?
Thanks for your question. We certainly have accepted non-CS/physics/math majors in the past. One of the key things to make sure you have is a good portfolio of Python/TensorFlow or PyTorch projects, and some practice deploying basic Flask apps. Devops is one of the biggest weaknesses people tend to have, particularly when they don’t come from a software development background.
So your next steps make sense to me. I’d recommend 1) complete the fastai course, 2) compete on Kaggle, and 3) get some practice with Flask. Feel free to shoot me an email if you’d like to follow up, I’m at jeremie[at]sharpestminds[dot]com.
@jeremie - is your “special deal” you spoke of also applicable to people that are taking the fast.ai courses entirely online via MOOC, or is that strictly for those that attended in-person? Secondly, can you please elaborate on the GitHub review step? If I haven’t been very active in posting to GitHub, what advice/tips could you provide?
Hi Devon, yes, it is available to MOOC participants as well. Regarding the GitHub review step, what we ask to see can depend somewhat on the results of the interview (we generally recommend application projects that align with gaps in your knowledge, so that the process of applying can itself have as much value as possible). Happy to go into more detail during the interview though!
Hello, how do I start a new post? There is no where I can find a start my own post button… please help thanks! I have questions regarding grouping column data to pass over the model.
