Great content. It’s so good to hear reliable and detailed information around these subject areas amidst many other channels that are selling the “ML Engineer in 2 months” dream. Love your channel Richard
Thank you so much! I am soon going to do a video on this very point... debunking the notions of being able to learn ML engineering or data science in such unrealistic time frames.
it is useful than other channel saying that degree is useless or something like that for data science, I have seen that most of real world data science jobs require PhD
Nice content! Im taking my BSc in Data Science at Lisbon-Portugal. The salaries in U.S are 5x time higher than in Portugal. We earn like 22k a year (in average), it's just stupid. I hope to get a chance to work in the U.S, you guys are really getting paid 🤣 Can you do a video about all the tech that you use in your Data Science projects? Keep the great work!
Hah, my gf tells me the same thing all the time... the U.S. is a great place to make money. Honestly, most of my tech TODAY is pretty boring (it's almost exclusively RStudio Server and Shiny Server), but that's not always been the case and I'm going to be personally changing responsibilities pretty significantly starting next week. I could certainly do a video at some point about how the tech I've used has changed and evolved as I've moved through my DS career to date though!
I think that ML description from Medium is quite accurate, and I would also include the data preprocessing and Data Engineering in a highly scalable, repeatable and tested way that withholds quality of data in both metadata and data values to support a sustainable model update
Richard, what about Data Science as the name of the general curriculum in the future (analogous to Computer Science), covering different company roles such as MLE, data engineers etc. (such as CS produces developers, QA engineers etc.)? The rising DS curricula at universities point into this direction.
I truly hope so! As far as my personal university was concerned, the Data Science program it adopted after I graduated has sort of hybridized statistics and computer science; however, I'm a little skeptical of the speed with which academia can adapt to real world trends like these.... hopefully I'm wrong!
Very interesting video, maybe the clearest I've seen so far at breaking down what exactly these positions are (from someone who knows their sh...) Thanks 🙌🏻🙌🏻
There is a new merge of Full stack ML engineers - that's a problem company will look for the Swiss knife guy who is willing to be Data analyst, ML engineer data engineer and Data scientist for the same amount of cash...
Probably statistics masters. The theoretical foundation will serve you incredibly well for understanding the intuitions behind ML; at producing and deploying these models later down the road, the CS bachelors will have served you incredibly well!
Hi Richard! Thanks a lot for your channel! Very interesting for absolute beginners like myself :) Right now I am digging through several books/tutorials. I can feel my progress in ML and understanding of the field. But here is the problem: I feel that I really need the community of learners and real projects to work on. But how to offer one's basic knowledge of data science and ML algorithms so that others would find it helpful even for free? Right now it seems that even volunteer positions are looking for super professionals. It would be very interesting to hear (or see) your suggestions on this problem. Hope it makes sense! Thanks in advance!
HIGHLY recommend going to Kaggle and doing some challenges, or at a bare minimum messing around with datasets. These are typically much cleaner datasets than those in the real world, but it's at least a way of getting some practical experience that many in the data science community do take seriously. I'll have guided, real ML problems on my channel eventually!
Good info. Thanks Richard. Can you please do a video on a double masters where a person does an CS undergrad, a one year masters in Data Analytics. Then an additional one year AI and Machine Learning masters. Thanks.
I'll do a video at some point soon about college degrees in general, yes! It's a little tough because it's very dependent on the specific school and program.
"I'll take work that I enjoy more any day over extra $10-20k." Well yes sir but your salary is probably in the top few percent of people on this planet ;) Thanks for the great vid.
This is a valid point. Everybody is going to have different values they assign to their time and money, both of which will encounter diminishing marginal returns.
Great video. Thank you for making this. I'm currently a junior CS major so I'm currently trying to figure out what exactly I want to do. Do you think you will make a video about grad school? That is an option I am currently looking into.
First off love the video ... but the "code monkey" quip... ugh stats nerds. Joking aside... People like different roles, but don't tear down people b/c they like the code. An ML engineer is very far away from a code monkey. Code monkeys are typically only found at medium+ businesses where someone finds the super repeatable task and focuses only on that task. My best example would be BI developer who only builds Tabular models and neglects ETL, Data Analysis, Reporting, and Schema design. I am technically a "data scientist" but I run our MLE vertical, we solve a wide array of problems and no one is coming on my team as a code monkey.
Data scientist is definitely the better role. After all, data scientist belongs to the business side, while machine learning engineer is merely a tech guy that they hire to do the time-consuming technical stuff that they don't want to do.
I hear you, that's totally understandable. To be fair I don't think you can get away from doing this entirely with ML engineering either. You're always going to have to talk, at least in some capacity, to programmers and other engineers about the nuances of your code and what's going on... but there's certainly far less story telling relative to data science where it's more core and fundamental to the field itself.
This really helps. The ML engineer sounds like the technical expert who knows the algorithms inside and out. This is what I want to do.
yea, same here
Great content. It’s so good to hear reliable and detailed information around these subject areas amidst many other channels that are selling the “ML Engineer in 2 months” dream. Love your channel Richard
Thank you so much! I am soon going to do a video on this very point... debunking the notions of being able to learn ML engineering or data science in such unrealistic time frames.
it is useful than other channel saying that degree is useless or something like that for data science, I have seen that most of real world data science jobs require PhD
Thanks million for your comprehensive explanation! It was brilliant. I suppose, in storytelling, you are the best. Thanks a lot
Wow, thank you!
I'm getting a masters in compsci in machine learning and software engineering.
I Love deep diving into code and solving hard problems
Still loving the hand gestures after all these years
Great video, I must admit it was more comfortable to me when using playback speed X1.25. Looking forward to seeing your other vids!
Clearest differentiation between DS and ML, good content!
Nice content! Im taking my BSc in Data Science at Lisbon-Portugal. The salaries in U.S are 5x time higher than in Portugal. We earn like 22k a year (in average), it's just stupid. I hope to get a chance to work in the U.S, you guys are really getting paid 🤣
Can you do a video about all the tech that you use in your Data Science projects?
Keep the great work!
Hah, my gf tells me the same thing all the time... the U.S. is a great place to make money.
Honestly, most of my tech TODAY is pretty boring (it's almost exclusively RStudio Server and Shiny Server), but that's not always been the case and I'm going to be personally changing responsibilities pretty significantly starting next week. I could certainly do a video at some point about how the tech I've used has changed and evolved as I've moved through my DS career to date though!
Great insights, exactly what I was looking for! Thank you!
You're very welcome!
Keep posting I just discovered your channel. Chin up mate.
Nice balance. Intense but not annoying. Bravo
That's what I strive to do. Thanks!
I think that ML description from Medium is quite accurate, and I would also include the data preprocessing and Data Engineering in a highly scalable, repeatable and tested way that withholds quality of data in both metadata and data values to support a sustainable model update
Really appreciate these videos dude, keep up the good work!
Glad you like them, many more videos to come this year!
Richard, what about Data Science as the name of the general curriculum in the future (analogous to Computer Science), covering different company roles such as MLE, data engineers etc. (such as CS produces developers, QA engineers etc.)? The rising DS curricula at universities point into this direction.
I truly hope so! As far as my personal university was concerned, the Data Science program it adopted after I graduated has sort of hybridized statistics and computer science; however, I'm a little skeptical of the speed with which academia can adapt to real world trends like these.... hopefully I'm wrong!
Very interesting video, maybe the clearest I've seen so far at breaking down what exactly these positions are (from someone who knows their sh...)
Thanks 🙌🏻🙌🏻
My pleasure! It'll only be more important to know in the future!
Sister, which one has more scope in future AI and ML or AI and datascience ,past few days I am in extreme dilemma kindly help me please
There is a new merge of Full stack ML engineers - that's a problem company will look for the Swiss knife guy who is willing to be Data analyst, ML engineer data engineer and Data scientist for the same amount of cash...
If i have a cs bachelors and i want to be an ml engineer, would you recommend a statistics masters or a cs degree that focuses on ml?
Probably statistics masters. The theoretical foundation will serve you incredibly well for understanding the intuitions behind ML; at producing and deploying these models later down the road, the CS bachelors will have served you incredibly well!
Hi Richard! Thanks a lot for your channel! Very interesting for absolute beginners like myself :) Right now I am digging through several books/tutorials. I can feel my progress in ML and understanding of the field. But here is the problem: I feel that I really need the community of learners and real projects to work on.
But how to offer one's basic knowledge of data science and ML algorithms so that others would find it helpful even for free? Right now it seems that even volunteer positions are looking for super professionals. It would be very interesting to hear (or see) your suggestions on this problem. Hope it makes sense! Thanks in advance!
HIGHLY recommend going to Kaggle and doing some challenges, or at a bare minimum messing around with datasets. These are typically much cleaner datasets than those in the real world, but it's at least a way of getting some practical experience that many in the data science community do take seriously. I'll have guided, real ML problems on my channel eventually!
@@RichardOnData Thanks for your reply Richard! Also, I would appreciate examples of real ML problems on your channel!
Good info. Thanks Richard.
Can you please do a video on a double masters
where a person does an CS undergrad,
a one year masters in Data Analytics.
Then an additional one year AI and Machine Learning masters.
Thanks.
I'll do a video at some point soon about college degrees in general, yes! It's a little tough because it's very dependent on the specific school and program.
"I'll take work that I enjoy more any day over extra $10-20k."
Well yes sir but your salary is probably in the top few percent of people on this planet ;)
Thanks for the great vid.
This is a valid point. Everybody is going to have different values they assign to their time and money, both of which will encounter diminishing marginal returns.
Great video. Thank you for making this. I'm currently a junior CS major so I'm currently trying to figure out what exactly I want to do. Do you think you will make a video about grad school? That is an option I am currently looking into.
If you'd be interested in a video on how to figure out if a grad school program is good, I'd be happy to do that!
First off love the video ... but the "code monkey" quip... ugh stats nerds. Joking aside... People like different roles, but don't tear down people b/c they like the code. An ML engineer is very far away from a code monkey. Code monkeys are typically only found at medium+ businesses where someone finds the super repeatable task and focuses only on that task. My best example would be BI developer who only builds Tabular models and neglects ETL, Data Analysis, Reporting, and Schema design. I am technically a "data scientist" but I run our MLE vertical, we solve a wide array of problems and no one is coming on my team as a code monkey.
Watching this video ater the ChatGPT strom
Data scientist is definitely the better role. After all, data scientist belongs to the business side, while machine learning engineer is merely a tech guy that they hire to do the time-consuming technical stuff that they don't want to do.
Everyone needs to read and digest this comment
No, most of the time data scientist is just a glorified analyst. They make dashboards. Ml engineers make systems.
@@ashleigh3021yeah I agree. data scientists seem to be just glorified statisticians while the ML engineers are the ones putting models into production
I should probably be a ML engineer. Don't really like telling story.
I hear you, that's totally understandable. To be fair I don't think you can get away from doing this entirely with ML engineering either. You're always going to have to talk, at least in some capacity, to programmers and other engineers about the nuances of your code and what's going on... but there's certainly far less story telling relative to data science where it's more core and fundamental to the field itself.
Cool video, but geeezzz.. your voice......
What's wrong?
@@RichardOnData Great 👍
@@RichardOnDataignore prolly a troll
Data scientist is a dead job… the future is data analyst, data engineer, and ML engineer.