More on Full Stack Data Science 👇 👉 Series Playlist: ruclips.net/p/PLz-ep5RbHosWmAt-AMK0MBgh3GeSvbCmL 📰 Read more: medium.com/towards-data-science/the-4-hats-of-a-full-stack-data-scientist-5b916bd2f079?sk=2d60946532c55d7c4f6502a8e73e7b52
Great question. AI Engineer seems to be a new one. I've mainly seen this from data science or ML engineering freelancers rebranding themselves for a non-technical audience. So they will likely have a similar skillset to a full-stack data scientist (as I describe it here). The AI Product Manager is one step beyond a full-stack data scientist in that they implement products rather than projects. This requires additional considerations such as sales, marketing, finding product market fit, and other business skills.
I agree. Product manager consider what and why, while engineers consider how. However, I'd say the project manager lives in between these two roles and considers all 3 questions.
Thank you for this video. I am biostatistician interested in datascience. I have a master degree in machine learning but not working in datascience project yet except on my personnal project during my free time. I have experieces in data ingeneering (mainly structured data: relationnal database). I have some knowledge in in machine learning. I participated once to Kaggle competition. I have alread made a Rshiny app and dockerized it. I am interested in deploying a ML model for just a fun. What framework would you recommend me first. I had began learning Django, but I am wondering I should rather go for FastAPI or streamlit or Flask.
What you need to learn depends on what your goals are. If you want to get a data science job you may not need to learn any of these skills. If you want to do more ML engineering learning FastAPI or Flask might help. If you want to freelance and deliver simple UI's for your models maybe you could learn streamlit or gradio. I don't know many (if any) data scientists using Django. Hope that helps!
from what I've seen, most ML engineers will have these data engineer and product management skills anyway, thus meaning a Machine Learning Engineer is equivalent to a Full-Stack Data Scientist. Theres also a specialist role on the rise called the MLOps Engineer though. Would be great to make a vid on that maybe.
I’m definitely still learning but here’s my quick background 👇 I was a researcher for 3.5 years. Worked as a data scientist for 1 year at Toyota. Quit that to do independent consulting.
More on Full Stack Data Science 👇
👉 Series Playlist: ruclips.net/p/PLz-ep5RbHosWmAt-AMK0MBgh3GeSvbCmL
📰 Read more: medium.com/towards-data-science/the-4-hats-of-a-full-stack-data-scientist-5b916bd2f079?sk=2d60946532c55d7c4f6502a8e73e7b52
Awesome! Can't wait! 😀
Thanks! Your anticipation is a good motivator for me :)
@@ShawhinTalebi I will always be anticipating then ☺
Thanks fp differentiating these roles in the data science 🔭 workspaces.
Your message sticks 🏒 right
It’s up to the viewers to implement the message or not. Shaw your videos are informative and you write good quality content. Keep it up!
This was a fantastic video. Been super interested in picking up the skills to become a FSDS - and this is a great starting point!
Thanks, hope the series helpful :)
Looking forward to the next videos in the series!
This is awesome. Thank you
Thank you for sharing...🎉
Thank you! great learning platform.
Thank you for your clear explanation!!!
Looking forward to the next videos!
Great video
Hey Shaw - Great video. But there are also an AI Engineer role & AI Product Manager roles. Where does it fit in?
Great question. AI Engineer seems to be a new one. I've mainly seen this from data science or ML engineering freelancers rebranding themselves for a non-technical audience. So they will likely have a similar skillset to a full-stack data scientist (as I describe it here).
The AI Product Manager is one step beyond a full-stack data scientist in that they implement products rather than projects. This requires additional considerations such as sales, marketing, finding product market fit, and other business skills.
A good overview but I think Product Manager rarely defines the How. That’s defined by the Engineer and the Scientist!
I agree. Product manager consider what and why, while engineers consider how.
However, I'd say the project manager lives in between these two roles and considers all 3 questions.
Thank you for this video. I am biostatistician interested in datascience. I have a master degree in machine learning but not working in datascience project yet except on my personnal project during my free time. I have experieces in data ingeneering (mainly structured data: relationnal database). I have some knowledge in in machine learning. I participated once to Kaggle competition. I have alread made a Rshiny app and dockerized it. I am interested in deploying a ML model for just a fun. What framework would you recommend me first. I had began learning Django, but I am wondering I should rather go for FastAPI or streamlit or Flask.
What you need to learn depends on what your goals are. If you want to get a data science job you may not need to learn any of these skills. If you want to do more ML engineering learning FastAPI or Flask might help. If you want to freelance and deliver simple UI's for your models maybe you could learn streamlit or gradio. I don't know many (if any) data scientists using Django.
Hope that helps!
from what I've seen, most ML engineers will have these data engineer and product management skills anyway, thus meaning a Machine Learning Engineer is equivalent to a Full-Stack Data Scientist.
Theres also a specialist role on the rise called the MLOps Engineer though. Would be great to make a vid on that maybe.
I could see that. Most MLEs these days are recovering data scientists XD.
❤
excuse me but he has not been in any REAL data science positions (writer, youtuber, ...). so i don't think your suggestions are relevant at all.
I’m definitely still learning but here’s my quick background 👇
I was a researcher for 3.5 years. Worked as a data scientist for 1 year at Toyota. Quit that to do independent consulting.
That's not experience.
Found the clowns in the comments