I am a seasoned data professional and I can tell you that I want to be a peasant, leave these jobs and live as peacefully as I can very far from the city growing vegetables and fruits.
1. Data jobs are not affected by recent lay off 2. Python, SQL, AWS,Azure, Spark, Tableau remains the tops skills to learn. 3. AI engineers for LLM more than ML engineers. 4. Freelancing 5. Low code tools.
In this day and age, networking while having a decent portfolio is just about the only way to enter this kind of job market. Trying on my own I easily spent a year looking. All I had to do was mention something to my brother, who knew someone in a nice position at a nice company, and bam the next day I spoke to the guy in person and landed an internship without him even properly looking into me. Welcome to 2024, where hard work sometimes means absolutely nothing when you know the right people...now I get to fight imposter syndrome instead of looking for a job haha (communication skills can help you bypass a lot of tough things too though. My ability to relate to people and keep things easy and fun are probably the only reason the guy didn't decide to look further into me after we met in person, and I've had other family members who are in 'hiring' positions say the same. I'm considered academically stupid and bottom-of-the-barrel, but being a great communicator singlehandedly changed all that. Obviously there's quite a bit of luck in play with all that, just so whoever is reading this doesn't feel deceived lol.
At 2022, i started to research about data roles and your videos was so inspiring for me, now im working as a machine Learning engineer, and is great to back to see you @Thu Vu, thank you so much. All that you mentioned in this video is true, i love the line that separates the Machine Learning engineer and AI engineer, is the API line, its really true and funny. But i´d like to add something focused on ML engineers. The maths, the back propagation, the kmean models and the metrics of finetunning is so usefull to understand how works the ML and DL models, derivatives is everything. Thank you so much @Thu Vu.
For someone who is getting serious with data as a career choice, your channel is very helpful and your video quality has improved a lot. Very insightful content..
Do you have a video on how someone beginning their data journey with SQL and Python can find practice questions/projects that can sharpen their skills. These projects can be either free or paid.
Thank you so much, I'm so appreciated of this. Regarding the practice questions/ projects, I'm creating exactly these as part of my new Python for DS/AI projects course. I expect to be launching it in a few weeks 🎉
I didn't go over the entire video, but I can tell you this: Every Tom, Jane, and Julietta nowadays know or claim to know Python and SQL, and the ratio is totally off. For every job that requires a Python person, there are about 2000 claimers for that job. It is no longer about knowing things; there is a lot more in play, including favoritism and other factors that may not be fair.
Suggesting to learn SQL and python to find data jobs is very similar to telling people to do "Self improvement" to find partners lol. When you have almost everyone who is self improving, at some point they will reach a ceiling that cannot be surpassed, at which point, genetics, favoritism, biases etc all play more important roles than your knowledge or hard work.
@@Ghostrider-ul7xn having the skills is the bare minimum. its much more important to bullshit your way to get a job. like in dating, being bold and confident, overselling your self goes a long way
I feel like being good at what you do is one of the most important things because people often say they can do something but usually they can barely do it as oppose to being excellent at it.
Prompt engineering is hot right now but trust me, that demand is transitory. In the future, LLMs will be sophisticated enough that prompt engineering will not be required. Instead spend more time learning foundational machine learning skills beyond LLMs and prompts. Build deep domain knowledge in an industry or business segment. There is a huge demand for people who have the technical skills and the business domain expertise, and this demand will continue to grow in the foreseeable future.
Exactly. Been building a small business with a team of ‘business excellence’ guys coupled with tech guys. Works perfectly (most of the times tech guys start appearing only after like 3-4 months in the project)
I'm currently in a career shift moving from general supply chain, to data science. I really appreciated this video, and it's a great reminder of how much there is to learn haha
Another thing is...Tech Companies are no longer paying 200k plus salaries..like handing out confetti....those days are gone. Seen so many people on UA-cam boasting about their easy work life and tech stock options and even turning it down and wanting more. Hubris....
Fully agree with SQL as indoctrinating analysts into critical ways of thinking of high volume data in terms of relational algebra. Apart from AI/MO, even for operational research, relational algebra *is* available in 4GLs like Python, but it's far more expedient in SQL (and is the focus of SQL). Once you have experience in the concepts and practice, you can battle the syntax and navigate the APIs of Python packages, but trying to do both can stunt progress in both. Also fully agree that technical skills need to be complemented with domain knowledge.
Im a recruiter specializing in data and AI roles specifically in the BFSI space. I appreciate her analysis. Let me add one piece of advice. Companies want data employees to show they can last at an employer longer than 18 months. Stop the job hopping. I know too many highly talented unemployed people that moved too much. Now they are in trouble willing to take whatever they can
Thanks for reminding us that the fundamentals matter even in a changing market. Focus on your skills, build a strong portfolio and network! That's the winning combination. 👍
As a software developer & data analyst, I am confident that data jobs won't be replaced easily comparing to software jobs. Data analysis requires more intense attention. I can write poor code when I am underslept, it would still work but it won't be the best practise. When I am underslept, one simple mistake in data analytics results in very important metrics being calculated wrongly, making the whole report useless sometimes. One comma, one number destorys the report.
@@eto38581 I have a masters degree in Demography and Social Statistics so I have a good understanding of data. My question is, is Data science tougher to learn than software engineer? Should I stick with data analysis?
@@eto38581 really CS degree?? I have BBA and MBA i wanted to be a data analyst i am a fresher right now.. there is no much companies that hires for data analyst
Hello Thu, the video gave me some motivation and hope thanks to the idea of becoming an AI Engineer. But why would an AI Engineer need to know stats, differential equations, advanced deep learning , and advanced Python and advanced SQL (as suggested at 8:00) if they will be using pre-trained models and pre-built tools? I can see why one would need to know the basics. I'm particularly curious to know why the Calculus and Linear Algebra are necessary, as the math is the main reason why I want to get into Data Science.
All jobs are data driven and nothing will completely replace them. My humble advice to all humans is to get a job or self-employee and start using data. The pressure is on employers to find suitable data workers competent or not. e.g. am an experienced data analyst but doing side hustles on the side while improving my skills every day and looking for data related opportunity... Lets get to work
Data jobs are getting , more and more automated. I think getting into the career of automation of various jobs might be the only job that is evolving and will evolve rapidly with AI. Most tasks will also get automated by ai creating another ai for other tasks. Eventually jobs with creative interests, major problem solving skills will remain relevant.
Interviewer: are you proficient in python? Interviewee: No, I am intermediate...but don't worry, I work all the time with my AI assistant who is proficient in python. I am proficient in domain knowledge though.
Lovely and insightful video as usual Thu. About job and job data, I think also that one of the problems is that companies in specific sectors that are a bit behind in terms of Data strategy/data savvy(like the financial and investment sector/s for example) they post job profiles and job specs that include 1000000 skills requested because they don't have clear the type of profile they want so they look (again, this is a very simplified example.. to try to be short in the comment) for people that have technical skills (coding, SQL, statistics, math) , business domain, data interpretation and data storytelling skills and also skills on how to talk to key stakeholders and management. So people are sometimes afraid to apply because they cannot have all these skills at the same time. They are confused and they demotivate some people to apply. Sorry for the long post
You're absolutely right, this is a problem in the industry. I recently read the book "The Big Con" and it has very eloquently pointed out that many companies/ organisations turned to consulting firms and pay a ton because they have no clue what to do and what kind of expertise they need 😅
Hello Thu, I am an international student in Canada pursuing CS and currently in my fourth year, I am working on my Data portfolio to get into DS. I am doing a QA internship, I thought that my QA exp wouldn't contribute much to my profile as a Data professional, but your video has broadened my view a lot and provided insightful points into the field's trend. It is hard right now to get a foot in the door, but I won't give up on my DS goals. Thank you so much and wish you all the best on growing your channel.
I personally think data management and data governance professionals will be in very high demand in the years to come, with most medium sized companies trying to go AI native. Data strategy is becoming increasingly necessary. Especially with growing concerns about data privacy, protection, and just the extra large volumes. After i saw what happened with MTN in Nigeria some years back, i realised how big of a deal data governance is going to be, now that AI is involved.
Wow Thu this is very insightful and a well done video. Thanks for creating! I appreciate your video is informative and well-researched! There are a lot of DS/ML/AI clickbait videos but this video was truly great information end to end. Subscribing now!
There is ONE thing that everybody who wants to get into the field should know... IS NOT FOR EVERYBODY. You need to be willing to put long hours, great at dealing with lots of math and being quick at thinking/implementing solutions. If you don't have them, one or more of these three scenarious are going to happen: either you won't know whatever is you are doing 50% of the time, or you won't know how to explain things prompting people to wonder wth is that you do, or worst, your incompetency will be revealed sooner or later by others who have these 3.
I think that managing a spreadsheet (eg Excel) is and will be necessary. An essential part of data work is to make short-scale proofs in every step of the cycle, and Excel is the best tool for do that due to its capability for manage essay and error tests. But it's an "internal-use" tool: the product that you deliver is never an Excel file. I guess that is the reason for its "low-demand"
Good analysis...👍However it's definitely worth adding a regional context to the data... Are the trends US vs Europe Vs rest of the world... How do the trends differ across regions etc...
Hi, I am from Brazil. I love coding. I course statistics and have master degree in Public Health. I work with Python, R, SQL and C++, but here We have so little oportunity. I was working in a hospital, but was laid off. I would like go abroud to have more oportunities.
Thank you for great contributions to the community and make me realise to contribute something to the community. So I started recently contributing to the community with SQL interview preparation, problem and solution series. Soon I will contribute many Thank you.
Been working with data for 3-4 years now. I mainly use sql. Okay I do use python sometimes for pivot tables, and if I am too lazy to start turning a csv/excel file into a table in a database. I really don't understand what is the benefits of writing sql commands in python? querying directly on the database is much faster, and you don't have to deal with a sht ton of csv/excel files on your laptop. and okay you might have some cool libraries and for webscraping beautifulsoup is amazing But why would you write sql commands in python? Can you give me one good reason to why I should start writing sql commands in python? I think this whole idea doesn't make sense to me.
I am a newbie in this field, but as far as i know, we can visualize data from sql server directly in python this can help automate stuff without actually repeatedly exporting to excel file
Generalizations are not usually 100 pc accurate across the board. where I am the change has not been significant. we still do much of our data jobs the traditional way... i have gone around and usage of AI is still too low. Even basic things like excel power tools are rarely used
Very useful indeed! Thank you so much for creating this video Thu Vu. Great content!👍 Excited to have found your channel. I plan to be an avid visitor of your channel for sure.
Hi, I'm in the process of getting admission in MSc in IT for Business Data Analytics from IBS Budapest. I'm keen to get a Job in the same area, what should I do and what should I learn from the beginning? I'm a Digital Marketing professional and you know it's saturated and with fewer Jobs. Thanks 👍
Thanks for this. I noticed though that some of the graphs you present that use datanerd as a source are not available at the site. That site seems to summarize skills and pay but in aggregate. That is, on that site I don't see anyway to reproduce the charts your have in sections 1 and 2 of your associated notebook and report. Thanks,
I saw ppl who call themselves data analysists and all they do is watch football match and count the number of touches a player has during the game and they keep reporting that to a cloud server which TV stations use. Many others are also doing the same job tracking the other players from the same game.
Chào Thu, video của bạn làm rất hay và bổ ích. Vương có công ty làm về phần mềm và marketing ở Houston Texas, Vương muốn nhờ bạn làm consultant mảng data và Ai cho cty Vương. Làm sao để Vương có thể liên lạc được với bạn.
What do you think of Berkeley's Data Science program? It's cool that they're opening a new College of Data Science and Statistics to expand the program.
Hi, Thu Vu just wonder what is application name that you use for workflow of project. If i am not wrong on one of your videos you used it to know who work on what and make revision on project, drag and drop based on status task. I really want to know and I need it. I would really appreciate yor help. Thank you.
How are we avoiding duplicate, triplicate and even quadruple postings of the same job being counted?? I am not convinced we have a “real” and true count of job postings; especially with 3rd party job sites popping up and then ending up on sites like Indeed.
Right now there is more jobs in France for data engineering than for data scientist. They talking about data modeling, efficient storage with partitioning, ETL, distributed/Big Data computing.... these all the skill set required for Data Engineering.
Hey there, thank you for watching! Check out the full data report in Datalore 👉 jb.gg/datalore-notebook
Wow, thanks for sharing the notebook! This is going to be super helpful for practicing data science reports
1 - Be Good / 2 - Have a strong Portfolio / 3 - Network.
Perfect!
Thank you! I'd like to tip you 13 minutes!
how do you network in this field?
@@GoodByeSkyHarborLive beg and lick peoples shoes
❤
Resign from data analytics and go to software engineer jobs!
I am a seasoned data professional and I can tell you that I want to be a peasant, leave these jobs and live as peacefully as I can very far from the city growing vegetables and fruits.
Same
What if your crop fails?
@@disarchitected I should have a stash for emergencia and if nothing works then I die
i had those exact same thoughts over my 12 years in analytics especially while traveling and meeting ppl who are so happy and stress free
@@disarchitected Then we will eat pickled vegetables and cured meats. We will also have a variety of crops, not just corn.
1. Data jobs are not affected by recent lay off
2. Python, SQL, AWS,Azure, Spark, Tableau remains the tops skills to learn.
3. AI engineers for LLM more than ML engineers.
4. Freelancing
5. Low code tools.
Thank you for writing down what the trends are
Resign from data analytics and go to software engineer jobs!
LLM means?
In this day and age, networking while having a decent portfolio is just about the only way to enter this kind of job market. Trying on my own I easily spent a year looking. All I had to do was mention something to my brother, who knew someone in a nice position at a nice company, and bam the next day I spoke to the guy in person and landed an internship without him even properly looking into me. Welcome to 2024, where hard work sometimes means absolutely nothing when you know the right people...now I get to fight imposter syndrome instead of looking for a job haha
(communication skills can help you bypass a lot of tough things too though. My ability to relate to people and keep things easy and fun are probably the only reason the guy didn't decide to look further into me after we met in person, and I've had other family members who are in 'hiring' positions say the same. I'm considered academically stupid and bottom-of-the-barrel, but being a great communicator singlehandedly changed all that. Obviously there's quite a bit of luck in play with all that, just so whoever is reading this doesn't feel deceived lol.
At 2022, i started to research about data roles and your videos was so inspiring for me, now im working as a machine Learning engineer, and is great to back to see you @Thu Vu, thank you so much. All that you mentioned in this video is true, i love the line that separates the Machine Learning engineer and AI engineer, is the API line, its really true and funny. But i´d like to add something focused on ML engineers. The maths, the back propagation, the kmean models and the metrics of finetunning is so usefull to understand how works the ML and DL models, derivatives is everything. Thank you so much @Thu Vu.
Wow that’s awesome! Congrats on your journey 🎉. Thanks for sharing your thoughts!
For someone who is getting serious with data as a career choice, your channel is very helpful and your video quality has improved a lot. Very insightful content..
Do you have a video on how someone beginning their data journey with SQL and Python can find practice questions/projects that can sharpen their skills. These projects can be either free or paid.
Thank you so much, I'm so appreciated of this. Regarding the practice questions/ projects, I'm creating exactly these as part of my new Python for DS/AI projects course. I expect to be launching it in a few weeks 🎉
@@Thuvu5 Great.. Looking forward to your course. Can't wait.
@@Thuvu5 so learning python for DS/AI will be very different than learning for programming/CS?
is it on UA-cam?@@Thuvu5
I really admire your channel, Thu! Wish you great health to keep up the great work!
Aw I appreciate that! Thank you for watching, wish you all the best too! 🤗
I didn't go over the entire video, but I can tell you this: Every Tom, Jane, and Julietta nowadays know or claim to know Python and SQL, and the ratio is totally off. For every job that requires a Python person, there are about 2000 claimers for that job. It is no longer about knowing things; there is a lot more in play, including favoritism and other factors that may not be fair.
Suggesting to learn SQL and python to find data jobs is very similar to telling people to do "Self improvement" to find partners lol. When you have almost everyone who is self improving, at some point they will reach a ceiling that cannot be surpassed, at which point, genetics, favoritism, biases etc all play more important roles than your knowledge or hard work.
Better join Army. Even if you die you won't regret it.
@@Ghostrider-ul7xn what do u suggest to improve the chances ?
I have the same thoughts. Everyone claims they know Python, SQL, Tableau, etc. so this piece of advice is not really helpful.
@@Ghostrider-ul7xn having the skills is the bare minimum. its much more important to bullshit your way to get a job. like in dating, being bold and confident, overselling your self goes a long way
I feel like being good at what you do is one of the most important things because people often say they can do something but usually they can barely do it as oppose to being excellent at it.
Prompt engineering is hot right now but trust me, that demand is transitory. In the future, LLMs will be sophisticated enough that prompt engineering will not be required.
Instead spend more time learning foundational machine learning skills beyond LLMs and prompts. Build deep domain knowledge in an industry or business segment. There is a huge demand for people who have the technical skills and the business domain expertise, and this demand will continue to grow in the foreseeable future.
Could you elaborate more please about the deep domain knowledge ...
DSPy is already changing the field
Exactly. Been building a small business with a team of ‘business excellence’ guys coupled with tech guys. Works perfectly (most of the times tech guys start appearing only after like 3-4 months in the project)
@@nada-bz1pghe just wanted to sound smart 🤓 he thinks we all can be amongst the elites.
Feel free to elaborate and provide specific job roles/titles.
Raising chickens is so relaxing. They give you eggs too.
Thanks!
Python and SQL are 👑
Great research, Thu! 🙌
Thanks Luke ❤️. Thank you for creating such a valuable job database for us data nerds 🎉
I'm currently in a career shift moving from general supply chain, to data science. I really appreciated this video, and it's a great reminder of how much there is to learn haha
Offshore freelancing is a big thing too, companies can find good analysts by a quarter of the US salaries
Girl, I'm a Data Scientist myself, but still new in the field. I didn't know I needed this video! Thanks for sharing❤
Great to hear! Thanks for watching 🤗
Hi
Thank you for your extensive and deep research and then sharing it!!
Another thing is...Tech Companies are no longer paying 200k plus salaries..like handing out confetti....those days are gone.
Seen so many people on UA-cam boasting about their easy work life and tech stock options and even turning it down and wanting more.
Hubris....
Fully agree with SQL as indoctrinating analysts into critical ways of thinking of high volume data in terms of relational algebra. Apart from AI/MO, even for operational research, relational algebra *is* available in 4GLs like Python, but it's far more expedient in SQL (and is the focus of SQL). Once you have experience in the concepts and practice, you can battle the syntax and navigate the APIs of Python packages, but trying to do both can stunt progress in both.
Also fully agree that technical skills need to be complemented with domain knowledge.
Im a recruiter specializing in data and AI roles specifically in the BFSI space. I appreciate her analysis. Let me add one piece of advice. Companies want data employees to show they can last at an employer longer than 18 months. Stop the job hopping. I know too many highly talented unemployed people that moved too much. Now they are in trouble willing to take whatever they can
Thanks for reminding us that the fundamentals matter even in a changing market. Focus on your skills, build a strong portfolio and network! That's the winning combination. 👍
As a software developer & data analyst, I am confident that data jobs won't be replaced easily comparing to software jobs. Data analysis requires more intense attention. I can write poor code when I am underslept, it would still work but it won't be the best practise. When I am underslept, one simple mistake in data analytics results in very important metrics being calculated wrongly, making the whole report useless sometimes. One comma, one number destorys the report.
Which one is easier to grasp between software engineer and data analysis or scientist
@@OluwajuwonloOWOJORI get a CS degree first. you will be able to do all of them. don't even bother without a degree at this point.
@@eto38581 I have a masters degree in Demography and Social Statistics so I have a good understanding of data. My question is, is Data science tougher to learn than software engineer? Should I stick with data analysis?
@@eto38581 really CS degree?? I have BBA and MBA i wanted to be a data analyst i am a fresher right now.. there is no much companies that hires for data analyst
@@eto38581is a data science degree as valuable as cs degree
Hello Thu, the video gave me some motivation and hope thanks to the idea of becoming an AI Engineer. But why would an AI Engineer need to know stats, differential equations, advanced deep learning , and advanced Python and advanced SQL (as suggested at 8:00) if they will be using pre-trained models and pre-built tools? I can see why one would need to know the basics. I'm particularly curious to know why the Calculus and Linear Algebra are necessary, as the math is the main reason why I want to get into Data Science.
All jobs are data driven and nothing will completely replace them. My humble advice to all humans is to get a job or self-employee and start using data. The pressure is on employers to find suitable data workers competent or not. e.g. am an experienced data analyst but doing side hustles on the side while improving my skills every day and looking for data related opportunity... Lets get to work
Data jobs are getting , more and more automated. I think getting into the career of automation of various jobs might be the only job that is evolving and will evolve rapidly with AI. Most tasks will also get automated by ai creating another ai for other tasks. Eventually jobs with creative interests, major problem solving skills will remain relevant.
Thanks for such an informative video Thu. Thanks for making the points too clear. Now I feel good about looking into the job market.
If enough people make similar videos I can go one level deeper by analyzing data about analyzing data
Interviewer: are you proficient in python?
Interviewee: No, I am intermediate...but don't worry, I work all the time with my AI assistant who is proficient in python. I am proficient in domain knowledge though.
does or can this trick work in real life? I always have that very question in me as I use AI to help me with some queries or code
This is a much-needed info Thu, Thanks for making this💯💯💯
Lovely and insightful video as usual Thu. About job and job data, I think also that one of the problems is that companies in specific sectors that are a bit behind in terms of Data strategy/data savvy(like the financial and investment sector/s for example) they post job profiles and job specs that include 1000000 skills requested because they don't have clear the type of profile they want so they look (again, this is a very simplified example.. to try to be short in the comment) for people that have technical skills (coding, SQL, statistics, math) , business domain, data interpretation and data storytelling skills and also skills on how to talk to key stakeholders and management. So people are sometimes afraid to apply because they cannot have all these skills at the same time. They are confused and they demotivate some people to apply. Sorry for the long post
You're absolutely right, this is a problem in the industry. I recently read the book "The Big Con" and it has very eloquently pointed out that many companies/ organisations turned to consulting firms and pay a ton because they have no clue what to do and what kind of expertise they need 😅
We can use the DOL OOH as a guideline, not a prediction about job prospects.
Hello Thu, I am an international student in Canada pursuing CS and currently in my fourth year, I am working on my Data portfolio to get into DS. I am doing a QA internship, I thought that my QA exp wouldn't contribute much to my profile as a Data professional, but your video has broadened my view a lot and provided insightful points into the field's trend. It is hard right now to get a foot in the door, but I won't give up on my DS goals. Thank you so much and wish you all the best on growing your channel.
@kimnganphanngoc597 How does QA help in Data analytics?
@@yuva204 you can check the video again at 8:25
Ui. Chị là người Việt Nam ạ 😍😍😍. Em cũng dự định học Thạc sĩ AI ở nước ngoài. Rất may mắn khi tìm thấy kênh của chị ạ.❤❤❤
Amazing analysis Thu! I really admire your amazing insights ❤
I just discovered your channel, and your content is clean ! Cheers
Great video with alot of great insights! Thank you!
Thank you so much! Glad you enjoyed it 🤗
I personally think data management and data governance professionals will be in very high demand in the years to come, with most medium sized companies trying to go AI native.
Data strategy is becoming increasingly necessary.
Especially with growing concerns about data privacy, protection, and just the extra large volumes.
After i saw what happened with MTN in Nigeria some years back, i realised how big of a deal data governance is going to be, now that AI is involved.
Impressive research! just got me more motivated.
Calm voice and insightful video❤😊
Thank you for making this video. This will be very helpful for my son.
Wow Thu this is very insightful and a well done video. Thanks for creating!
I appreciate your video is informative and well-researched! There are a lot of DS/ML/AI clickbait videos but this video was truly great information end to end.
Subscribing now!
just discovered you, and your explanation is wow. I have already watched a few of your videos :)
Great Video. Very relevant for anyone interested in Data Science or A.I. Engineering
There is ONE thing that everybody who wants to get into the field should know... IS NOT FOR EVERYBODY. You need to be willing to put long hours, great at dealing with lots of math and being quick at thinking/implementing solutions. If you don't have them, one or more of these three scenarious are going to happen: either you won't know whatever is you are doing 50% of the time, or you won't know how to explain things prompting people to wonder wth is that you do, or worst, your incompetency will be revealed sooner or later by others who have these 3.
Great Video ! , Thanks For Sharing your Insight with Us
3:20 I'm surprised Excel is 3rd lowest on the list...I thought it was also important for data analysis along with SQL and Python, is it not anymore?
I think that managing a spreadsheet (eg Excel) is and will be necessary. An essential part of data work is to make short-scale proofs in every step of the cycle, and Excel is the best tool for do that due to its capability for manage essay and error tests. But it's an "internal-use" tool: the product that you deliver is never an Excel file. I guess that is the reason for its "low-demand"
Wow this is so much great information, thank you!
Good analysis...👍However it's definitely worth adding a regional context to the data... Are the trends US vs Europe Vs rest of the world... How do the trends differ across regions etc...
This was a great post. It always amazes me how persons on UK give their time to post such great content.
weird comment
Hi, I am from Brazil. I love coding. I course statistics and have master degree in Public Health. I work with Python, R, SQL and C++, but here We have so little oportunity. I was working in a hospital, but was laid off. I would like go abroud to have more oportunities.
Thanks to content creators like yourself anyone can enter the industry which is both good and bad.
At 4:00 he crammed so much relational db concepts yet omitting the most fundamental: normalization.
how i wish we can have no-code or low-code tools already rolled out so programming wasn't so mind wracking
Thank you for great contributions to the community and make me realise to contribute something to the community. So I started recently contributing to the community with SQL interview preparation, problem and solution series. Soon I will contribute many Thank you.
Thank you for your work, you are really helping out many people out there !
Been working with data for 3-4 years now. I mainly use sql. Okay I do use python sometimes for pivot tables, and if I am too lazy to start turning a csv/excel file into a table in a database.
I really don't understand what is the benefits of writing sql commands in python? querying directly on the database is much faster, and you don't have to deal with a sht ton of csv/excel files on your laptop. and okay you might have some cool libraries and for webscraping beautifulsoup is amazing But why would you write sql commands in python?
Can you give me one good reason to why I should start writing sql commands in python? I think this whole idea doesn't make sense to me.
I am a newbie in this field, but as far as i know, we can visualize data from sql server directly in python this can help automate stuff without actually repeatedly exporting to excel file
Great video! Just subscribed.
New sub; learning so much from your content.
Awesome content!
It was really an amazing and informative video. Can you please make a video on how to learn about domain knowledge for data analysts as a fresher?
Hi! Thank you very much for doing this insightful research and sharing it!
Thank you for your tips at the end, I really appreciate you
Great video, thanks :)
think about moving to developing or poor countries, if you are gold here, you would be diamond in those countries.
Generalizations are not usually 100 pc accurate across the board. where I am the change has not been significant. we still do much of our data jobs the traditional way... i have gone around and usage of AI is still too low. Even basic things like excel power tools are rarely used
by the time we get the grip of AI and start applying for jobs, there will be another skill that will supersede AI 😂
Not really. At the end of the day it's all math, programming and statistics
Is it☹️
@@PavithraGH30 hey don't get discouraged. i was just kidding. anything that you learn will be useful in the future 😊
farming ? 😂
Ok thank yu@@saravanakumar6617
Thank you so much as a cs student it helps a lot ! Great video . Amazing content as usual. Keep it up :) thank you so much 😊
Aw I appreciate that, thanks so much for your kind comment! 🤩
cs is overrated and saturated to the point many CS graduates are still unemployed for almost a year now. Lmfao. Good choice bud.
Very useful indeed! Thank you so much for creating this video Thu Vu. Great content!👍 Excited to have found your channel. I plan to be an avid visitor of your channel for sure.
your content and collected data was amazing
i have advice, please put the points in description or chapters since it will help people who wants to pinpoint between the time series faster
Perfect video!
Great insights!
Thank you for your research and sharing it ❤
Lol, I laughed when you said "Data Cleaning Ninja", because you know there's some ETL expert out there who does data cleaning all day!
Hey Matt, haha that’s absolutely true!
Hi, I'm in the process of getting admission in MSc in IT for Business Data Analytics from IBS Budapest.
I'm keen to get a Job in the same area, what should I do and what should I learn from the beginning? I'm a Digital Marketing professional and you know it's saturated and with fewer Jobs.
Thanks 👍
Thanks for this. I noticed though that some of the graphs you present that use datanerd as a source are not available at the site. That site seems to summarize skills and pay but in aggregate. That is, on that site I don't see anyway to reproduce the charts your have in sections 1 and 2 of your associated notebook and report. Thanks,
Thank you Thu Vu!
Thank you for coming back for the video ❤️
Thank you so much for your insightful sharing chi
I saw ppl who call themselves data analysists and all they do is watch football match and count the number of touches a player has during the game and they keep reporting that to a cloud server which TV stations use. Many others are also doing the same job tracking the other players from the same game.
Hi, can you make a video on becoming a market research analyst, with emphasis on skills to focus on?
Really Enjoyed this video
thank you so much for the info, pls do a notion tour💫
So I do not need SQL to make me an AI engineer right?
Chào Thu, video của bạn làm rất hay và bổ ích. Vương có công ty làm về phần mềm và marketing ở Houston Texas, Vương muốn nhờ bạn làm consultant mảng data và Ai cho cty Vương. Làm sao để Vương có thể liên lạc được với bạn.
Very useful information 🎉
This video is gold!
Can you teach us the framework that you use to research a topic and construct your ideas for presentation to the public?
What do you think of Berkeley's Data Science program? It's cool that they're opening a new College of Data Science and Statistics to expand the program.
The Data Cleaning Ninja was too good😂
you're a life saver.
This video really motivates me to work hard...🙂
Click like if you got a cert, was self taught, got a professionally written resume and couldn’t get a job.
I'm curious how a small business on the corner might offer data freelance work but otherwise this is great thanks for the insights!
Hi, Thu Vu just wonder what is application name that you use for workflow of project. If i am not wrong on one of your videos you used it to know who work on what and make revision on project, drag and drop based on status task. I really want to know and I need it. I would really appreciate yor help. Thank you.
Hey, do you mean Notion? 😊
I really like the insights you've shared in this video!
Cảm ơn chị Thư 🥰
How are we avoiding duplicate, triplicate and even quadruple postings of the same job being counted?? I am not convinced we have a “real” and true count of job postings; especially with 3rd party job sites popping up and then ending up on sites like Indeed.
90 percent of jobs on Indeed r fake.
This is a very goated comment. Every single job appears more than once always.
@@prico3358 true. So how are we avoiding the duplicates? I generally am not convinced that the numbers are not inflated, even by error.
i am a dev who is looking to get into big data as It feels its a bit safer then software development in terms of AI replacement. Hope I am right
Thank you so much for the video. Do you have any findings about **Data Engineering** specifically?
Right now there is more jobs in France for data engineering than for data scientist.
They talking about data modeling, efficient storage with partitioning, ETL, distributed/Big Data computing.... these all the skill set required for Data Engineering.
Do we have any websites where I can download Sample Data and questions on it for PowerBi