That is great advice to learn stats. An employer will see someone they can upskill quickly and adapt to variety of needs. In stats, I'd study survival analysis, regression, time series forecasting methods, and exploratory stats such as pca/factor analysis methods & cluster analysis methods, then ANOVA, CHAID (decent primer into trees). You will later find ML more approachable. I'm not a data scientist, but find the data science skillset useful for a lot of tasks, especially automation and ML. BTW, thanks for the VS Code & python setup video, I'm finally enjoying python :)
I'm surprised you didn't mention domain specific knowledge -- if you want to work in health, then take a course in pharmacology and physiology and genetics -- if you want to work in finance take a course in economics, finance and investing -- if want to work for the US government then figure out doing what and take a course in earth science, climatology, or space studies
Yep, I don't disagree with any of this. In many instances, domain specific knowledge is honestly more important than any of the things I mentioned in this video. A lot of people when they're just starting out don't necessarily care as much about which industry they're getting into, they just want a job. A lot of domain knowledge also comes down to understanding your business's data. That can be pretty difficult to do unless you're literally already employed.
For certain science and engineering fields, also get the basics of modeling and simulation. This could also be taught in courses with names like differential equations, numerical methods/computation/analysis, computational science & engineering, computational physics/chemistry/biology/... and so on. If you'll be dealing with physical measurements, also look for courses on/containing signal processing, measurement & instrumentation, filtering, parameter estimation, inverse problems, uncertainty quantification, etc. There you'll usually see probability and statistics coming up too. In addition to Python and/or R you might work with MATLAB or Julia. On the machine learning side you might end up working with data-driven differential equations (e.g. SciML).
Great to see you back and congratulations on the new adventures! My journey continues and I am still reeling from the growth of this field. I can see the light at the end of the tunnel for my stats master but need to come up with a thesis since comps suck cuz I suck at high stakes, one time shot kinda tests. Its an applied stats masters so I want to apply it and I am better at writing and talking and programming, especially now that ChatGPT and other LLM's are around. I am taking a natural language programming class this semester and excited about all the new tools around to play with. Looking forward to your upcoming content and how you have adapted to this new environment. Best!
Hey Richard, it's great that you are back! I' ve been following your channel for years, ever since I researched how SAS ranks as data science software in 2020s 😆 I recently discovered the field of Process Mining and was amazed. I am currently working on its introduction into corporation that I work for 😄 It would be great to hear how do you see that area fits into data science ecosystem and today's job market. Even a separate video on process mining would be awesome. Keep up the good workp 👏
Hi Sir thanks for yet another great video. can you make a video on the most widely used ML tools. I have a background of chemistry and Environmental science on a masters level, I have started learning r through reading book and watching you tube videos. do you think I have a future on data science. I'm from Ethiopia.
I would argue, that Pyhton is a little bit harder to learn for total beginners in programming. I R you have R-Studio and you don't need to take care of compiling, the current version of python, etc.. But I also have the feeling, that in general the economic sector is developing more towards python, but R will stay relevant because universitys will stay with it and therefore teach it.
I actually agree with all of these points (especially on Python versioning), but I’ve heard many people say they found Python to be the easier of the two. I definitely don’t think R is going anywhere, given so much is down stream from what universities do.
@@RichardOnData Not to mention many universities start with C/C++ or Java. So grasping Python next is a piece of cake. And starting with harder programming language will make the future outcome much easier.
@@RichardOnData two years ago maybe three I was in role where we were mainly using R and I had your videos playing in the background while cleaning my apartment and cooking
@@RichardOnData I don't think it meaningfully makes the videos less consise but at the same time in my original comment I did mention that it did look somewhat amateurish (due to looking a little generic) while also being somewhat earnest in an admirable way which also made it kind of enjoyable. I deleted that part of the comment because I didn't want to be too harsh, but that's also my honest feedback put as constructively as I can.
I use R and I studied SQL on the fly in my first job. unfortunately I feel like i shouldve invest more time in studying python. I became really good and native in R but all my collogues use python
Yeah, there's absolutely no question Python opens you up to more total opportunities and the ability to build more things. You can have a good career and make a lot of money in R only (especially if you're good in shiny), but most tech companies are out of reach unless you're strong in Python.
That is great advice to learn stats. An employer will see someone they can upskill quickly and adapt to variety of needs. In stats, I'd study survival analysis, regression, time series forecasting methods, and exploratory stats such as pca/factor analysis methods & cluster analysis methods, then ANOVA, CHAID (decent primer into trees). You will later find ML more approachable. I'm not a data scientist, but find the data science skillset useful for a lot of tasks, especially automation and ML. BTW, thanks for the VS Code & python setup video, I'm finally enjoying python :)
Why are you giving advice on how to break into data science if you’re not a data scientist??
I'm surprised you didn't mention domain specific knowledge -- if you want to work in health, then take a course in pharmacology and physiology and genetics -- if you want to work in finance take a course in economics, finance and investing -- if want to work for the US government then figure out doing what and take a course in earth science, climatology, or space studies
Definitely agree there about getting some domain specific knowledge
Yep, I don't disagree with any of this. In many instances, domain specific knowledge is honestly more important than any of the things I mentioned in this video. A lot of people when they're just starting out don't necessarily care as much about which industry they're getting into, they just want a job. A lot of domain knowledge also comes down to understanding your business's data. That can be pretty difficult to do unless you're literally already employed.
For certain science and engineering fields, also get the basics of modeling and simulation. This could also be taught in courses with names like differential equations, numerical methods/computation/analysis, computational science & engineering, computational physics/chemistry/biology/... and so on. If you'll be dealing with physical measurements, also look for courses on/containing signal processing, measurement & instrumentation, filtering, parameter estimation, inverse problems, uncertainty quantification, etc. There you'll usually see probability and statistics coming up too. In addition to Python and/or R you might work with MATLAB or Julia. On the machine learning side you might end up working with data-driven differential equations (e.g. SciML).
I really like your videos man. They have a rhythm... have a beginning, middle and end (conclusion)
Hah, well thank you, I try
Great to see you back and congratulations on the new adventures! My journey continues and I am still reeling from the growth of this field. I can see the light at the end of the tunnel for my stats master but need to come up with a thesis since comps suck cuz I suck at high stakes, one time shot kinda tests. Its an applied stats masters so I want to apply it and I am better at writing and talking and programming, especially now that ChatGPT and other LLM's are around. I am taking a natural language programming class this semester and excited about all the new tools around to play with. Looking forward to your upcoming content and how you have adapted to this new environment. Best!
Best of luck to you! I was fortunate with my stats masters that there was no thesis to do. Hard courses but once you pass them you’re good to go.
Who wins in a 1v1 battle - Yamcha or Freddy Krueger ?
I have to go with Freddy Krueger on this one.
ultra instinct Yamcha stomps
Yamcha gets bodied by everyone, Freddy would put him in a blender and have him for breakfast.
Great to see you again Richar, I really like the way to explain things!
Thank you!
Hey Richard, it's great that you are back! I' ve been following your channel for years, ever since I researched how SAS ranks as data science software in 2020s 😆 I recently discovered the field of Process Mining and was amazed. I am currently working on its introduction into corporation that I work for 😄 It would be great to hear how do you see that area fits into data science ecosystem and today's job market. Even a separate video on process mining would be awesome. Keep up the good workp 👏
Great to see you back!
Great to be back, too!
thanks RIchard :)
You're welcome!
Hi Sir thanks for yet another great video. can you make a video on the most widely used ML tools. I have a background of chemistry and Environmental science on a masters level, I have started learning r through reading book and watching you tube videos. do you think I have a future on data science. I'm from Ethiopia.
I would argue, that Pyhton is a little bit harder to learn for total beginners in programming.
I R you have R-Studio and you don't need to take care of compiling, the current version of python, etc..
But I also have the feeling, that in general the economic sector is developing more towards python, but R will stay relevant because universitys will stay with it and therefore teach it.
I actually agree with all of these points (especially on Python versioning), but I’ve heard many people say they found Python to be the easier of the two. I definitely don’t think R is going anywhere, given so much is down stream from what universities do.
@@RichardOnData Not to mention many universities start with C/C++ or Java. So grasping Python next is a piece of cake. And starting with harder programming language will make the future outcome much easier.
Hi Richard, do employers actually look at or care about portfolio projects. I've read mixed feedback on this. What are your thoughts on this?
Yeah certainly not all of them care. I’ve had some explicitly ask to see an old project. It’s one of those things that certainly can’t hurt you.
Man I was wondering what happened to you
Life got busy, but here I am...
@@RichardOnData two years ago maybe three I was in role where we were mainly using R and I had your videos playing in the background while cleaning my apartment and cooking
What happened to the intro?
Generally have been trying to keep the videos a little tighter and more concise, but if you have a strong feeling about it, could bring it back!
@@RichardOnData I don't think it meaningfully makes the videos less consise but at the same time in my original comment I did mention that it did look somewhat amateurish (due to looking a little generic) while also being somewhat earnest in an admirable way which also made it kind of enjoyable. I deleted that part of the comment because I didn't want to be too harsh, but that's also my honest feedback put as constructively as I can.
@@dangernoodle2868 All valid points. I may create a new updated one in the near future then!
good
Better than bad
I use R and I studied SQL on the fly in my first job. unfortunately I feel like i shouldve invest more time in studying python. I became really good and native in R but all my collogues use python
R feels like entering to data analysis but for data science (8k$/month jobs) you really need python and advanced math
Yeah, there's absolutely no question Python opens you up to more total opportunities and the ability to build more things. You can have a good career and make a lot of money in R only (especially if you're good in shiny), but most tech companies are out of reach unless you're strong in Python.
"promosm"