I've just launched a starter course for those looking to get their feet wet. The First-Principles Framework is available for just $9.99, and you can secure it here today: www.gptlearninghub.ai/first-principles-framework
I think data science is a good stepping stone if you want to work on ML problems in the industry. There's this weird hierarchy of data analyst -> data scientist -> MLEng that you have to climb in the tech world. Just keep at it.
Data scientist to ML Engineer? The roles are fundamentally different. One is research focused, the other is engineering focused. To do well in one, means deviating from the other, since they tackle fundamentally different parts of a business problem.
I am currently doing a data science internship. I agree with what you said in the video. Now I feel running the model is not the most difficult. Finding the right variables from the gazillion different tables in databricks, joining and preparing the input data tables for the specific problem is the most time consuming especially when the documentation is not updated
This sounds like what happens to anyone who gets a degree and then gets a job: you come to learn that the job isn't a continuation of what school required you to do, and that 95% of what you're doing is new. I understand if this is disappointing, but that's the reality, and advertising it as "harsh" or unique to data science is (perhaps unintentionally so) sensationalizing.
I have a master's degree in maths and Ive never really used any knowledge from there during my 4 years as a ds. I would say my job is more like a sql dev who knows when and how to use python.
Hey Dev, do you think its a good choice to learn Java/Go like majorly backend cause it interests me as an undergrad rn if or should only go for ML cause AI is in boom
@@sambhavmishra5423 Learning backend engineering is still 100% beneficial, especially if it interests you! If you learn both ML and backend engineering, then ML engineering is one viable career path 💪
Isn't collecting and preparing the data, the job of a data engineer? Or do companies expect data scientists to be proficient at data engineering technologies?
I've just launched a starter course for those looking to get their feet wet. The First-Principles Framework is available for just $9.99, and you can secure it here today: www.gptlearninghub.ai/first-principles-framework
I think data science is a good stepping stone if you want to work on ML problems in the industry. There's this weird hierarchy of data analyst -> data scientist -> MLEng that you have to climb in the tech world. Just keep at it.
💪
Data scientist to ML Engineer? The roles are fundamentally different. One is research focused, the other is engineering focused. To do well in one, means deviating from the other, since they tackle fundamentally different parts of a business problem.
I am currently doing a data science internship. I agree with what you said in the video. Now I feel running the model is not the most difficult. Finding the right variables from the gazillion different tables in databricks, joining and preparing the input data tables for the specific problem is the most time consuming especially when the documentation is not updated
wdym right variable? right variable for what? do you mean target feature which will help in predicting output?
Thanks for sharing your experience!
This sounds like what happens to anyone who gets a degree and then gets a job: you come to learn that the job isn't a continuation of what school required you to do, and that 95% of what you're doing is new. I understand if this is disappointing, but that's the reality, and advertising it as "harsh" or unique to data science is (perhaps unintentionally so) sensationalizing.
Definitely not unique to data science!
Join a statistics group in a quant or acturial firm. Those are the only corporates doing ML.
I have a master's degree in maths and Ive never really used any knowledge from there during my 4 years as a ds. I would say my job is more like a sql dev who knows when and how to use python.
A master's in maths is really interesting! Thanks for sharing your experience.
Master's in math and a background in data science/data engineering? You could apply to quant positions.
@@adriboy01 Why would I do that?
@@-es2bf Up to you man, it was just a suggestion based on your skillset. Nobody's forcing you.
Where can I find the platform you made with NeetCode?
All the problems and my solution videos can be found here! neetcode.io/practice?subpage=practice&tab=coreSkills&topic=Machine%20Learning
Hey Dev, do you think its a good choice to learn Java/Go like majorly backend cause it interests me as an undergrad rn if or should only go for ML cause AI is in boom
@@sambhavmishra5423 Learning backend engineering is still 100% beneficial, especially if it interests you! If you learn both ML and backend engineering, then ML engineering is one viable career path 💪
Definitely don’t restrict yourself to ML only!
How can i download the blueprint please someone wxplain
It's too expensive for Indian Middle-class Students!!!
$300 = ₹ 25218.56!!! Too much
@@suvrodeepdas1220 Check out my new product! It’s just $10 and comes with a lifetime money-back guarantee, just in case you don’t love it.
Can you please mentor me dev I don't know how to start and develop my self
Isn't collecting and preparing the data, the job of a data engineer? Or do companies expect data scientists to be proficient at data engineering technologies?