As a current college student, I really appreciate the breakdown of the different roles and responsibilities for Data Science. Keep up the good work and I would love to learn more about DS.
I'm just wondering if I should choose data science as a career or not and this video is just to great. I mean explanation is really nice. It was helpful for me.
Jesus is the only way to healing, restoration and salvation to all souls. Please turn to him and he will change your life, depression into delight, soul heading from hell to heaven all because of what he did on the cross “Whoever calls upon the name of the Lord shall be saved” Romans 10:13
@@CofeeAuLait So who crunch the data, we can consider it a part of the job? since in many times we have to solve some problemes related to data exploring, for exeple some data sets are not really complete, so there are many tools to process missing data
Word: Data Scientist Description: Data Scientist are people who uses data to create impact for the organization through insights, product recommendation and etc. Where to find a Data Scientist: You will often see data scientist in public places like bridges, if there are too many people in the bridge, look for the person dancing goofily. That's the data scientist.
Oh my goodness, this was the best explanation of a Data Scientist I've heard so far! The breakdown of what a Data Scientist would do at different companies was insanely helpful and clarifying for me. Much appreciated!!
Consistent nomenclature would be amazing, but startups are such havoc on that notion! Thanks for breaking down the startup vs midsize vs deep pocket lingo. It's easier to guess the actual role scope by company size and industry with a good breakdown like this.
Could you do a video showing some actual day to day activities on the job. Basically putting some of the things videos mentioned into context with some real life examples would be great (I understand this may be tough because of company rules on privacy/security etc) but anything of the sort is appreciated!
Completely agree, as a data scientist in telco company most of time what i needed i just SQL to retrieve data, Tableau to make quick insight, Python with Jupyter Notebook to build model and experiment with dataset after assessing from data insight and business knowledge.
Can you explain what you mean with the Python part? My working experience is similar to yours; It starts at retrieving data with SQL but ends in Power BI for analysis. What does Tableau for example lack in comparison to Python?
@@BeunckensJeroen I am interested in it as well, I am a beginner in DS just freshly graduated. I don't understand why python is needed when tableu can pretty much generate visualizations given the data is clean and all.
@@hmZ93094 I don't know how tableau works but if I am not mistaken it is a software built for data visualisation, which means it is not as flexible as using Python where you can do whatever you want if you control the language and packages such as matplotlib
I wish I saw this 6 months ago! I've been trying to transition careers from physics to "data science" and after not having much luck despite what I thought to be very similar methods used in my former career, now its becoming clear why my resume is getting nowhere... I've focused on the top too much, haven't showcased my whole pyramid. Thank you bro!
Hey Cadmus! Great to hear you’re trying to transition 😊 Fellow data scientist and small TH-camr here, I’ve got a lot of videos up on my channel that talks about how to break into the industry and my advice, maybe it could help you out? :)
I'm a college student wanting to explore this field. You're been a great help. I'd love to watch ur videos on the breakdown of the buzzwords...ml, ai, deep learning, neural networks etc... btw loved the video.
It's a breath of fresh having someone so simply express the breadth of this career field. An onslaught of technical terms do little but confuse the curious. I will now quote mine Einstein: “If you can't explain it to a six year old, you don't understand it yourself.” Good video friend!
Man I got a whole lot of value out of this video! I'm a young data scientist, I've worked at both a corporate and a start-up, and I hadn't seen this chart yet! Thanks!!
Such a concise, easy to understand, and thorough explanation you've got there. It can be understood clearly by someone like me, with no prior knowledge of what data science is and what it entails. Great content!
Hi Joma, Please make a series about the whole data science process using real open source data, explain every step in the pyramid while doing live coding. Explain the tasks and the tools used in real life. I think you might get millions of views for that, because it might be the first series of it's kind in TH-cam.
I would love to see the stream of steps taken with the pyramid that you just showed us. Like saying what are normallly the steps taken to implement models in big companies. That would be so cool!
I've been interested in the term "data science" and what it could mean for me, my hobbies and career, and your video has been a brilliant introduction. Thank you!
Published 4 years ago, but this is still helpful for many, like myself who is aspiring to be one and would like to know more before completely committing. Really really good explanation and breakdowns, and very comprehensible. Thank you for helping us clearing our thoughts and setting us on the right path!
@@brecamilla5451 im currently taking the course, still in my first year! so im on my way to become it. as far as i can tell, the modules ive been learning have been intriguing and seems applicable in the real life
@@khairilhaziq4215 oh that’s wonderful! so you like it? idk if i should start the course or not bc i’m scared i might not. but i think it is interesting so far from the video! also thanks for responding:)
@@brecamilla5451 most definitely. and the math gets harder at the years go on. i got stuck on Computational Maths, but finally got the ball rolling and now can understand the lessons better. there's other modules that also involve maths, and its to be expected, however Computational Maths is the only one i feel like mentioning bcs its the hardest so far
You are spot on about the low hanging fruit. I work for a medium size company and your explanation is exactly what I experience. And here I thought we were just lagging behind. 80% of my job is cleaning data. One of the key problems I find in companies that I worked for is legacy systems. It's crazy how much time we spend just dealing with legacy systems. Would be interested if that effect you work.
@@avgmean4187 Quite near but at the same time now the job scope is way wider. Back then they are called Statistician, Quantitative Analyst. And back then the main degree for this was either Stats or Economics, not Com Sci
One of the best definitions I have ever seen about what is Data Scince! Really helped me to see what companies could expect we to do, specially for those who cames from academia ❤
You really made my day!!! This is the first time I can understand the core history of Data Science and the definition of it. Before that I still wonder that what is the difference between Data scientist, analyst and so on. Its such a great overview of Data Science I've ever watched! Thank you so muchh
I was a neuroimaging and clinical research scientist. I'm changing careers. My experience, knowledge, and abilities in advanced stats, coding, problem-solving, and cleaning/analyzing/visualizing data hopefully will allow me to transition quickly into data science. That said, I've been confused as to what aspects of data science the majority of my time would be spent on. You cleared up a lot, things that other TH-camrs haven't touched. Really informative. Thanks.
I have a startup and I'm looking for a data scientist to join my team. This was very helpful. Especially to someone like me who didn't know all the capabilities of a data scientist.Great work Joma!
At my line of job, there is no DS, just SQL kids, any model that is not linear regression or contains more than 2 params is beyond the knowledge of the manager.
Maybe you can make a series on Business Consulting as a Data Scientist (types of problems, how to demonstrate value, relevant areas of expertise, etc)?
Wonderful! I agree your point that there is huge gap between hot “AI” “ML” and what industries need. GAFA born with data, and of course targeting the top of your triangle of needs. Most of the other industries and public sector still are still looking at the static reports. They need the correct ways to do data analytics, rather than chase “data science”. I just uploaded a case study demo of data analytics for normal company’s normal process.
This was super helpful! Thanks for explaining the nuances between the various responsibilities and how they play out in different roles at different size companies.
Thanks a lot for explaining the terminology associated with DS jobs at various levels of the hierarchy 👏 👍 Makes it much easier now to apply to the _right_ job titles, rather than accidentally to a similar-sounding job that one actually *doesn't* wanna apply for 🙂
The entire data science scene on TH-cam is one of the most convoluted I have ever come across. You guys use the most complicated programs and lingo and each one of you tells a different story about what data science is.
seriously where have you been in my life? I've been reading a lot to understand about data science and had a hard time understanding it, and watching your video giving me a clear view about what actually data science is! thank youuu so much!
Hi Joma, Please make a series about the whole data science process using real open source data, explain every step in the pyramid while doing live coding. Explain the tasks and the tools used in real life. I think you might get millions of views for that, because it might be the first series of it's kind in TH-cam.
This is the most complete explanation I have seen. Thank you so much. I am planning on going back to school and was a bit confused regarding DS but thank you again for putting this into a more complete, synthesize, and easy to understand explanation.
As a fellow data user, it seems to me that as I work more and more in data science and as a developer - we end up wearing many, many hats. Maybe especially so when you've skilled stacked for a few years. From reviewing, validating, and updating engineering initiatives, to managing a server, to answering ad hoc questions that just require research and a quick number crunch. I've gone from trying to understand massive SQL servers, to Tableau dashboards and cloud storage management, to being asked to prep a new pipeline of GA360 data into AWS. It's fun and stressful.
This is definitely the most concise, clear and informative video about this topic i've come across so far. Being a college student this video was very helpful and entertaining.
thanks dude for the awesome video! i just graduated in mechanical engineering but I kind of getting interested in venturing more in data science, so this video really helped a lot in understanding the overall role :)
You hit the nail right on the head buddy. I say this from an academic's perspective. When I look at data science for my faculty, I advocate designing and teaching subjects that engage students to think about real business problems and make recommendations backed up by data, information and presented well via visualisation techniques. However, you will be surprised how many University faculties are creating "Data Analytics" subjects that are really just rebadged finance, econometrics, programming or statistics units. They insert all the financial models, equations and calculations but have little to no analysis or analytics let alone any decision making.
I am a data scientist intern for an insurance company, primarily focus on the Analytics side. This is exactly I thought how Data Science is, and we should be clear there are some absolute differences between a data scientist, a data analyst, and a data engineer. Do your research and find out which area is in your interest.
Oh, and thanks, @joma !! Your vids have been super helpful fo understanding the industry landscape of DS, since I’m a new Graduate 🙏🏽 very much appreciated.
they're two completely different processes. A/B testing is about finding statistically significant differences in versions of products/services while minimizing the time/sample size needed to do so. Training and testing (and validation) are used to ensure your predictive models are not overfit--that they can generalize well to new, unseen data. But I suppose the concepts do intersect when you consider long-term use of predictive models--I have heard of companies that conduct A/B testing of different predictive models to judge when to replace old models with newer ones, given that over time the current data will begin to differ from the data used to initially train the model.
You might want to check the "A / B Testing: The Most Powerful Way to Turn Clicks Into Customers" book by Dan Siroker and Pete Koomen; the cofounders of Optimizely which is the leading company in A/B testing space: www.aioptify.com/best-ab-testing-books.php
It seems like a great career. I’m a financial analyst right now but I already know SQL and Power BI. I’d like to add Python and R to my repertoire so I can move to a role where I can combine my existing finance knowledge with data science
My recommendation is to provide more information and tutorials starting from the bottom of the pyramid and working your way towards the top of the pyramid. This is the best recommendation for those of us who would be a one man operation working toward becoming a multiple people organization. Thanks!
thank you! recently, i saw in my career path that I will have to choose between data scientist, data engineering, automation or development (traditional). well, in some videos some people say that data engineers will "connect" better with CEO's (or will by better paid), but, the things you can learn choosing data scientist are more "technical" in a way. they'll teach you mathematics, inference and integrals while in data engineering not. Saludos desde Chile!
Thank you so much for the insightful explanation. I would like to see what kind of portfolio we might need to prepare to start looking for a job as a Data Analyst. I'm very new to this, so this question might be quite naïve! Thank you once again :)
Data Science is a multidisciplinary field that involves extracting knowledge and insights from various types of data. It combines techniques from statistics, mathematics, computer science, and domain expertise to analyze and interpret complex datasets. The primary objective of data science is to gain meaningful information, patterns, and trends from the data to inform decision-making and solve real-world problems. Key components of Data Science include: Data Collection: Gathering data from different sources, which could be structured (e.g., databases, spreadsheets) or unstructured (e.g., text, images, videos). Data Cleaning and Preprocessing: Preparing the data for analysis by handling missing values, removing inconsistencies, and transforming it into a usable format. Exploratory Data Analysis (EDA): Performing initial analysis to understand the data's characteristics, distribution, and relationships between variables. Data Modeling: Developing mathematical and statistical models to represent patterns and relationships in the data. This can include machine learning algorithms for prediction, classification, clustering, etc. Evaluation and Validation: Assessing the performance and accuracy of the models using various metrics and validating them to ensure they generalize well to new data. Visualization: Communicating the findings and insights effectively through visual representations like graphs, charts, and dashboards. Interpretation and Decision-Making: Deriving actionable insights from the analysis and using them to make informed decisions and solve problems. Data Science is widely applicable across various industries, including finance, healthcare, marketing, technology, and more. It plays a crucial role in optimizing processes, understanding customer behavior, detecting anomalies, predicting future trends, and improving overall efficiency. In summary, Data Science is the practice of using data-driven methodologies and tools to discover valuable knowledge and make data-informed decisions, driving innovation and advancements across a broad range of fields.
Hi everyone, We are providing Data Science with Python course for free of cost. We will be covering each and every topic in detail from scratch. Subscribe below channel to keep learning. th-cam.com/channels/m4gqBFhMYGGIwAkLTRnXJA.html
Thank you so so so much for this information and clearing away so many doubts. Everyone keeps telling what Data Science is, but no one really told what it actually is and the breakdown. This makes things so much clear. Cheers!!!
Thanks Joma! After watching this video I regain my confidence to work in the industry. All other video mostly just either discouraging for very technicals or simply misleading, was feeling kinda dumb when I'm no expert in Deep Learning and want to work in the industry as a DA, Analytics. Thanks for clearing the clouds, mate! :D
Yes, please. I also want to know how to become a Data scientist with my Master's in Manufacturing Engineering ? Can i become a data scientist.? If yes, please suggest us online platforms that are helpful to get the knowledge and complete course.
@@madhanidevang3298 There's no such formula. With a Master degree I'm sure at this point you already know it's our job to educate ourselves. TL:DR: YES! YOU CAN but you have to find your way.
i think there are some analytic, data science job in Google too just like in facebook: careers.google.com/jobs#!t=jo&jid=/google/product-analyst-data-science-google-building-41-1600-amphitheatre-2527730235&
My life as data scientist: Wake up. Get to work by 10. Pull data Reshape data Pull data Model data Explore data *more rare* Build a ML model if necessary for project. Create batch procedure for project to run through AKS Before this I had to build and PoC Enterprise ML cloud infrastructure. Tools are PBI, ML Service, and ML Studio. I write code in R, Python, SQL, and PowerShell.
I like it. The struggle of a data scientist in a small company like the one I'm in though... small being net 2 billion dollar profit per year in the real estate industry... makes it where I dont get to do the *cool stuff* someone at Google Netflix Facebook or Amazon does, but i also have way more freedom to create my own projects because I'm basically the only subject matter expert there.
Thank you so much for your videos. Ever since I was a kid I wanted to be a computer scientist but while growing uo I discovered there are actually different branches to it. But you breaking this down gives me more knowledge of what I should branch into and learn more. I am in my third year in college and I am not going to lie it has been tough but I know it will get better with time. I have watched about 5 different videos just tonight that I found this channel, lol. Thanks again, Mr. Joma.
Two questions: 1. for beginner stage, what classes do you recommend to take in college? 2. Where do Data Translators fall in this pyramid? Thank you for the video... Very helpful.
I watched this video about 2 years ago, back than I didn’t understand anything about data science but knew clearly I want to learn more about this field. Watching this video back than was helpful but knowing what I know today (building some projects in ML during bootcamps and studying DS degree in college) made it absolutely clear now. I agree with the way you presented it and I like how you did it. It gave me better insights about a role I want to look for. Thank you for your valuable video.
Thank you for this. I am thinking of going back to school to become a Data Scientist, and this video helped me a lot to understand what a DS' job entails.
Just a random thought: Lol when you were knocking on her door I was like maybe that’s his sister. But when you guys were in the car and you were thanking her for driving you and she said stfu I was like yep that’s his sister! Lol reminds me so much of me and my brothers! 😂😂😂
This was very helpful. I am in my senior year as a information science major with a concentration in data science/analytics . I’m currently in an internship working with big data, but everything is so confusing when I am trying to understand what I will be doing on an everyday basis in my career. This video has given me A lot of insight 🙏
First, I would like to thank you for the information. second, I would recommend you to make a series of videos addressing every step of that pyramid and what kind of talent needed/curriculum and maybe even the best place to learn them and the best place to start with. Thanks again.
these are what i watch when im depressed about my career at 1am
We gonna make it ...one day
Exactly, I am watching this at 12:33AM so to find my passion and purse an undergraduate programme.
Yes I am watching because I am bored of my job😂
SHUT UP, 1:45AM
Me at 1:10am
As a current college student, I really appreciate the breakdown of the different roles and responsibilities for Data Science. Keep up the good work and I would love to learn more about DS.
good luck randall!
I'm just wondering if I should choose data science as a career or not and this video is just to great. I mean explanation is really nice. It was helpful for me.
@@jomakaze awww
Things aren't funny anymore it's gay
Some people r saying that data science is going to vanish in just 5 years....bt don't listen to them...
Days worth of knowledge compressed in 11 minutes. Why isn't the world of youtube more like you. Thank you Joma.
Nothing against Joma, it's a great video, but "days of knowledge?"
Jesus is the only way to healing, restoration and salvation to all souls. Please turn to him and he will change your life, depression into delight, soul heading from hell to heaven all because of what he did on the cross
“Whoever calls upon the name of the Lord shall be saved” Romans 10:13
“What tools do you use... we don’t care”
Agreed, the job is not about crunching the data but to make an impact with it.
@@CofeeAuLait So who crunch the data, we can consider it a part of the job? since in many times we have to solve some problemes related to data exploring, for exeple some data sets are not really complete, so there are many tools to process missing data
Well, its called data science, and not data coding for a reason. Its about getting the job done, whatever means. simple as that.
I totally agree with you. Python, R, SAS ? That don’t matter ! the purpose is to find solution for the company
For many companies though, the tool does seem to matter
Word: Data Scientist
Description: Data Scientist are people who uses data to create impact for the organization through insights, product recommendation and etc.
Where to find a Data Scientist: You will often see data scientist in public places like bridges, if there are too many people in the bridge, look for the person dancing goofily. That's the data scientist.
😂😂
I read your comment first then watched video lmao
I'm the person who hit like to make it 500 under this comment
@@reeannfernandez242 hahaha awesome. I wonder who the 600th, 700th and so on would be or if they would comment. Haha!
lmao gold.
Oh my goodness, this was the best explanation of a Data Scientist I've heard so far! The breakdown of what a Data Scientist would do at different companies was insanely helpful and clarifying for me. Much appreciated!!
I love that you straight up started from the main idea without making it boring and long
This is definitely the most helpful video I’ve seen. Especially the hierarchy of needs for small, medium, and large companies! Thank you Joma.
Same to me! Benefited a lot from this video! Great job indeed.
Consistent nomenclature would be amazing, but startups are such havoc on that notion! Thanks for breaking down the startup vs midsize vs deep pocket lingo. It's easier to guess the actual role scope by company size and industry with a good breakdown like this.
Could you do a video showing some actual day to day activities on the job. Basically putting some of the things videos mentioned into context with some real life examples would be great (I understand this may be tough because of company rules on privacy/security etc) but anything of the sort is appreciated!
Completely agree, as a data scientist in telco company most of time what i needed i just SQL to retrieve data, Tableau to make quick insight, Python with Jupyter Notebook to build model and experiment with dataset after assessing from data insight and business knowledge.
What name company?
Can you explain what you mean with the Python part? My working experience is similar to yours; It starts at retrieving data with SQL but ends in Power BI for analysis. What does Tableau for example lack in comparison to Python?
@@BeunckensJeroen I am interested in it as well, I am a beginner in DS just freshly graduated. I don't understand why python is needed when tableu can pretty much generate visualizations given the data is clean and all.
You don't use R??
@@hmZ93094 I don't know how tableau works but if I am not mistaken it is a software built for data visualisation, which means it is not as flexible as using Python where you can do whatever you want if you control the language and packages such as matplotlib
I wish I saw this 6 months ago! I've been trying to transition careers from physics to "data science" and after not having much luck despite what I thought to be very similar methods used in my former career, now its becoming clear why my resume is getting nowhere... I've focused on the top too much, haven't showcased my whole pyramid. Thank you bro!
Hey Cadmus! Great to hear you’re trying to transition 😊 Fellow data scientist and small TH-camr here, I’ve got a lot of videos up on my channel that talks about how to break into the industry and my advice, maybe it could help you out? :)
my whole pyramid ( ͡° ͜ʖ ͡°)
How are things?
How are You?
How’s it goin?
Can we talk about the fact that he drove to the office to print off a chart and then FedEx it to himself 😂
That was genius!
Oh my god the real world moment was just incredible
you mean (driven) to the office by his ex!
Wait..what??!! :D
@@teedo76 hahaha I was about to say that 🤣🤣 that was the funniest part and he did everything with a serious poker face.🤭🤭
I'm a college student wanting to explore this field. You're been a great help. I'd love to watch ur videos on the breakdown of the buzzwords...ml, ai, deep learning, neural networks etc... btw loved the video.
It's a breath of fresh having someone so simply express the breadth of this career field. An onslaught of technical terms do little but confuse the curious. I will now quote mine Einstein: “If you can't explain it to a six year old, you don't understand it yourself.” Good video friend!
Man I got a whole lot of value out of this video! I'm a young data scientist, I've worked at both a corporate and a start-up, and I hadn't seen this chart yet! Thanks!!
Hey can you tell what task you get to do there pls
hi did you finish masters/phD before getting a fine job?
@@nicolecatacutan2757 heyyy cutie pie;)
do you like working as a data scientist?
The different camera angles and entrances were so different from Joma’s current video style. Informative video
Such a concise, easy to understand, and thorough explanation you've got there. It can be understood clearly by someone like me, with no prior knowledge of what data science is and what it entails. Great content!
Of course he is a data scientist thats his work literally
@@rudrapanchal5011 Nothing's wrong with a little encouragement and feedback, right? 😉
Show some hands-on stuff with python, pandas, numpy, matplotlib, sql, etc. like tasks you do on the job
100% need this
Agreed, the overview is great but would be even better to have hands on with more details
Hi Joma,
Please make a series about the whole data science process using real open source data, explain every step in the pyramid while doing live coding.
Explain the tasks and the tools used in real life.
I think you might get millions of views for that, because it might be the first series of it's kind in TH-cam.
yeah, I'd like to see that from the bottom of the pyramid all the way to the top
Stop asking like a child. And start working/searching instead of wanting someone to give all information for free.
I would love to see the stream of steps taken with the pyramid that you just showed us. Like saying what are normallly the steps taken to implement models in big companies. That would be so cool!
I've been interested in the term "data science" and what it could mean for me, my hobbies and career, and your video has been a brilliant introduction. Thank you!
A data scientist should be able to ask questions and should find the answers to it!
this is one of the most comprehensive and best resources i've seen
Published 4 years ago, but this is still helpful for many, like myself who is aspiring to be one and would like to know more before completely committing. Really really good explanation and breakdowns, and very comprehensible. Thank you for helping us clearing our thoughts and setting us on the right path!
hi! did you ever become a data scientist? just curious as i was looking to become one as well
@@brecamilla5451 im currently taking the course, still in my first year! so im on my way to become it. as far as i can tell, the modules ive been learning have been intriguing and seems applicable in the real life
@@khairilhaziq4215 oh that’s wonderful! so you like it? idk if i should start the course or not bc i’m scared i might not. but i think it is interesting so far from the video! also thanks for responding:)
@@khairilhaziq4215 is it a lot of math involved?
@@brecamilla5451 most definitely. and the math gets harder at the years go on. i got stuck on Computational Maths, but finally got the ball rolling and now can understand the lessons better. there's other modules that also involve maths, and its to be expected, however Computational Maths is the only one i feel like mentioning bcs its the hardest so far
You are spot on about the low hanging fruit. I work for a medium size company and your explanation is exactly what I experience. And here I thought we were just lagging behind.
80% of my job is cleaning data.
One of the key problems I find in companies that I worked for is legacy systems. It's crazy how much time we spend just dealing with legacy systems.
Would be interested if that effect you work.
Hello can i be a data scientist without university degree?
What problems did you face dealing with legacy systems? Any examples in mind?
2009: Statistics , 2019: Machine Learning, 10 years challenge
@ Data Science is just Applied Statistics rebranded
@@avgmean4187 Quite near but at the same time now the job scope is way wider. Back then they are called Statistician, Quantitative Analyst. And back then the main degree for this was either Stats or Economics, not Com Sci
@@avgmean4187 man you cracked that in a nutshell
One of the best definitions I have ever seen about what is Data Scince! Really helped me to see what companies could expect we to do, specially for those who cames from academia ❤
1:12 results of data science
lol
You really made my day!!! This is the first time I can understand the core history of Data Science and the definition of it. Before that I still wonder that what is the difference between Data scientist, analyst and so on. Its such a great overview of Data Science I've ever watched!
Thank you so muchh
I was a neuroimaging and clinical research scientist. I'm changing careers. My experience, knowledge, and abilities in advanced stats, coding, problem-solving, and cleaning/analyzing/visualizing data hopefully will allow me to transition quickly into data science. That said, I've been confused as to what aspects of data science the majority of my time would be spent on. You cleared up a lot, things that other TH-camrs haven't touched. Really informative. Thanks.
I can see that you've put a lot of thought into this video (very clever with the multiple prints lol). Great work!
sank yew sank yew
I have a startup and I'm looking for a data scientist to join my team. This was very helpful. Especially to someone like me who didn't know all the capabilities of a data scientist.Great work Joma!
Hi Dwight, still looking for one? Maybe I can help you out.
Check my lkdin profile: www.linkedin.com/in/marcossaturno
You realize when something is well done when it's both entertaining and useful! Thanks for the video
Joma... You're a beast. Thanks for the breakdown . Most accurate I've seen so far. Thanks
At my line of job, there is no DS, just SQL kids, any model that is not linear regression or contains more than 2 params is beyond the knowledge of the manager.
💀😂🙌🏼
Damnn💀
I know it's been 6 years since you've released this, but I absolutely loved this video man. Helped me a lot thank you.
the most mature 11-minutes-video on data science i've ever seen .. and the dance in the intro ,man i've repeated it like 86 times :"D
same man it was fire
Maybe you can make a series on Business Consulting as a Data Scientist (types of problems, how to demonstrate value, relevant areas of expertise, etc)?
this video definitely cleared my thoughts on DE and DS. Thanks Joma!
I would love to learn more about A/B Testing, as well as any advice for aspiring Data Science Analysts. Awesome channel, so glad I found it!
I second this notion, can we haz a video on A/B testing plz?
Wonderful! I agree your point that there is huge gap between hot “AI” “ML” and what industries need. GAFA born with data, and of course targeting the top of your triangle of needs. Most of the other industries and public sector still are still looking at the static reports. They need the correct ways to do data analytics, rather than chase “data science”. I just uploaded a case study demo of data analytics for normal company’s normal process.
link?
Yeah can you provide the link?
@@shreyasinha4980 watch his channel
I thought this would've been a Joma meme video and was surprised by how unironically helpful it is
This was super helpful! Thanks for explaining the nuances between the various responsibilities and how they play out in different roles at different size companies.
Thanks a lot for explaining the terminology associated with DS jobs at various levels of the hierarchy 👏 👍
Makes it much easier now to apply to the _right_ job titles, rather than accidentally to a similar-sounding job that one actually *doesn't* wanna apply for 🙂
The entire data science scene on TH-cam is one of the most convoluted I have ever come across. You guys use the most complicated programs and lingo and each one of you tells a different story about what data science is.
seriously where have you been in my life? I've been reading a lot to understand about data science and had a hard time understanding it, and watching your video giving me a clear view about what actually data science is! thank youuu so much!
Hi Joma,
Please make a series about the whole data science process using real open source data, explain every step in the pyramid while doing live coding.
Explain the tasks and the tools used in real life.
I think you might get millions of views for that, because it might be the first series of it's kind in TH-cam.
Thats 20k $ thanks
This is the most complete explanation I have seen. Thank you so much. I am planning on going back to school and was a bit confused regarding DS but thank you again for putting this into a more complete, synthesize, and easy to understand explanation.
Today I learned that I want to forever learn and become a research scientist
I would thoroughly enjoy hearing details about job duties on each level of the hierarchy... perhaps in a multi-part YuoTube video series?
I agree
As a fellow data user, it seems to me that as I work more and more in data science and as a developer - we end up wearing many, many hats. Maybe especially so when you've skilled stacked for a few years. From reviewing, validating, and updating engineering initiatives, to managing a server, to answering ad hoc questions that just require research and a quick number crunch.
I've gone from trying to understand massive SQL servers, to Tableau dashboards and cloud storage management, to being asked to prep a new pipeline of GA360 data into AWS.
It's fun and stressful.
This is definitely the most concise, clear and informative video about this topic i've come across so far. Being a college student this video was very helpful and entertaining.
thanks dude for the awesome video! i just graduated in mechanical engineering but I kind of getting interested in venturing more in data science, so this video really helped a lot in understanding the overall role :)
You hit the nail right on the head buddy.
I say this from an academic's perspective. When I look at data science for my faculty, I advocate designing and teaching subjects that engage students to think about real business problems and make recommendations backed up by data, information and presented well via visualisation techniques.
However, you will be surprised how many University faculties are creating "Data Analytics" subjects that are really just rebadged finance, econometrics, programming or statistics units. They insert all the financial models, equations and calculations but have little to no analysis or analytics let alone any decision making.
I am a data scientist intern for an insurance company, primarily focus on the Analytics side. This is exactly I thought how Data Science is, and we should be clear there are some absolute differences between a data scientist, a data analyst, and a data engineer. Do your research and find out which area is in your interest.
Can I be a data scientist with out a CS or college degree?
@@mashooraraf344 yes you can but having a cs degree really helps. There are a lot of math and statistics majors who work as data scientist as well.
Hello
Can do data science without doing matrix?
Would like to learn more about A/B Testing! Thanks :)
Ajay Vasisht +1 how is the process different from test/train? Is it just that A/B is done live?
Oh, and thanks, @joma !! Your vids have been super helpful fo understanding the industry landscape of DS, since I’m a new Graduate 🙏🏽 very much appreciated.
www.udacity.com/course/ab-testing--ud257 that might help!
they're two completely different processes. A/B testing is about finding statistically significant differences in versions of products/services while minimizing the time/sample size needed to do so. Training and testing (and validation) are used to ensure your predictive models are not overfit--that they can generalize well to new, unseen data. But I suppose the concepts do intersect when you consider long-term use of predictive models--I have heard of companies that conduct A/B testing of different predictive models to judge when to replace old models with newer ones, given that over time the current data will begin to differ from the data used to initially train the model.
You might want to check the "A / B Testing: The Most Powerful Way to Turn Clicks Into Customers" book by Dan Siroker and Pete Koomen; the cofounders of Optimizely which is the leading company in A/B testing space:
www.aioptify.com/best-ab-testing-books.php
That is such a fantastic breakdown of data science and how it scales to various sized business models! Thanks @JOMA TECH!
It seems like a great career. I’m a financial analyst right now but I already know SQL and Power BI. I’d like to add Python and R to my repertoire so I can move to a role where I can combine my existing finance knowledge with data science
Brendan Funny I’m reading this, because that’s what I want to do now. Learn Python a bit more.
ZEROKOOL-20 Good luck to you!
Brendan thanks, same to you.
"Thanks for driving...." "Shut the f*ck up"
I am subscribing because of that statement.
Me too.
Then I realized she was serious!
yeah that dude is a pushover and she was lucky he just needed a ride, couldn't be me lmao
@@onehungryboy9438 lol thats all fake dude lmao
what is her @ tho??
My recommendation is to provide more information and tutorials starting from the bottom of the pyramid and working your way towards the top of the pyramid. This is the best recommendation for those of us who would be a one man operation working toward becoming a multiple people organization. Thanks!
Thank you Joma for taking the time to breakdown and simplify what jobs full under Data Science. 👍🏼
This is a very informative video. And I totally agree with the perspectives you shared Joma
Hello, my name is Yang Qiao from Hong Kong, China, I hope to become friends with you, if you like, you can add my WhatsApp +852 66163679
Wow. Fantastic job articulating data science. Clear. Concise. Easy to follow. Thanks!
thank you! recently, i saw in my career path that I will have to choose between data scientist, data engineering, automation or development (traditional). well, in some videos some people say that data engineers will "connect" better with CEO's (or will by better paid), but, the things you can learn choosing data scientist are more "technical" in a way. they'll teach you mathematics, inference and integrals while in data engineering not. Saludos desde Chile!
Would love to see a video on the "Analytics" aspect of Data Science
the word "Impact" in the impact font is impactful.
Thank you for simplifying it all, I am currently doing what you are describing.
Thank you so much for the insightful explanation. I would like to see what kind of portfolio we might need to prepare to start looking for a job as a Data Analyst. I'm very new to this, so this question might be quite naïve!
Thank you once again :)
So helpful ! And non-superfluous. I like your low key approach. Thank you :)
I would like to learn more on A/B testing and analytics. Great videos educational and entertaining.
Your budget film making skills are on point.
1:36 William S. Cleveland wanted to bring data mining to NUTTER level!
Data Science is a multidisciplinary field that involves extracting knowledge and insights from various types of data. It combines techniques from statistics, mathematics, computer science, and domain expertise to analyze and interpret complex datasets. The primary objective of data science is to gain meaningful information, patterns, and trends from the data to inform decision-making and solve real-world problems.
Key components of Data Science include:
Data Collection: Gathering data from different sources, which could be structured (e.g., databases, spreadsheets) or unstructured (e.g., text, images, videos).
Data Cleaning and Preprocessing: Preparing the data for analysis by handling missing values, removing inconsistencies, and transforming it into a usable format.
Exploratory Data Analysis (EDA): Performing initial analysis to understand the data's characteristics, distribution, and relationships between variables.
Data Modeling: Developing mathematical and statistical models to represent patterns and relationships in the data. This can include machine learning algorithms for prediction, classification, clustering, etc.
Evaluation and Validation: Assessing the performance and accuracy of the models using various metrics and validating them to ensure they generalize well to new data.
Visualization: Communicating the findings and insights effectively through visual representations like graphs, charts, and dashboards.
Interpretation and Decision-Making: Deriving actionable insights from the analysis and using them to make informed decisions and solve problems.
Data Science is widely applicable across various industries, including finance, healthcare, marketing, technology, and more. It plays a crucial role in optimizing processes, understanding customer behavior, detecting anomalies, predicting future trends, and improving overall efficiency.
In summary, Data Science is the practice of using data-driven methodologies and tools to discover valuable knowledge and make data-informed decisions, driving innovation and advancements across a broad range of fields.
Would love to see videos about machine learning/data science core 🤖
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@Michel Tamgho thanks..just did
Thank you so so so much for this information and clearing away so many doubts. Everyone keeps telling what Data Science is, but no one really told what it actually is and the breakdown. This makes things so much clear. Cheers!!!
Thanks Joma! After watching this video I regain my confidence to work in the industry. All other video mostly just either discouraging for very technicals or simply misleading, was feeling kinda dumb when I'm no expert in Deep Learning and want to work in the industry as a DA, Analytics. Thanks for clearing the clouds, mate! :D
Make a video on Step by Step guide on how to be a Data Scientist / ML Engineering
Yeah, we need it.
Yes, please. I also want to know how to become a Data scientist with my Master's in Manufacturing Engineering ? Can i become a data scientist.? If yes, please suggest us online platforms that are helpful to get the knowledge and complete course.
@@madhanidevang3298 There's no such formula. With a Master degree I'm sure at this point you already know it's our job to educate ourselves.
TL:DR: YES! YOU CAN but you have to find your way.
Yes please
hey Joma!
Just want pop in and comment, this video is giving me a better understand about this job's responsibilities. Thanks Joma! :))
Very well edited :D
You had my attention for the whole video
Thanks for the driving to the office and FedX package delivery humor.
DS is different everywhere. At Google they build models, at Facebook they are data driven PMs.
That's a bit of a sweeping generalization...
i think there are some analytic, data science job in Google too just like in facebook: careers.google.com/jobs#!t=jo&jid=/google/product-analyst-data-science-google-building-41-1600-amphitheatre-2527730235&
Best video I cam across regarding Data Science family job roles...
Thanks Joma!
My life as data scientist:
Wake up.
Get to work by 10.
Pull data
Reshape data
Pull data
Model data
Explore data
*more rare*
Build a ML model if necessary for project.
Create batch procedure for project to run through AKS
Before this I had to build and PoC Enterprise ML cloud infrastructure. Tools are PBI, ML Service, and ML Studio. I write code in R, Python, SQL, and PowerShell.
do u like it ? or boring for u
I like it. The struggle of a data scientist in a small company like the one I'm in though... small being net 2 billion dollar profit per year in the real estate industry... makes it where I dont get to do the *cool stuff* someone at Google Netflix Facebook or Amazon does, but i also have way more freedom to create my own projects because I'm basically the only subject matter expert there.
Travis Long good job dude !!!!!
Boring job
Hey travis, I needed your help regarding machine learning. Could you just drop down your mail?
Thank you so much for your videos. Ever since I was a kid I wanted to be a computer scientist but while growing uo I discovered there are actually different branches to it. But you breaking this down gives me more knowledge of what I should branch into and learn more. I am in my third year in college and I am not going to lie it has been tough but I know it will get better with time. I have watched about 5 different videos just tonight that I found this channel, lol.
Thanks again, Mr. Joma.
Beautifully explained!
Two questions: 1. for beginner stage, what classes do you recommend to take in college? 2. Where do Data Translators fall in this pyramid?
Thank you for the video... Very helpful.
Did you find out what classes to take? Kinda in the same boat now lol
1:11 this is when you graduate from university of waterloo THIS THING HAD ME DYING.
I watched this video about 2 years ago, back than I didn’t understand anything about data science but knew clearly I want to learn more about this field. Watching this video back than was helpful but knowing what I know today (building some projects in ML during bootcamps and studying DS degree in college) made it absolutely clear now. I agree with the way you presented it and I like how you did it. It gave me better insights about a role I want to look for. Thank you for your valuable video.
Thank you for this. I am thinking of going back to school to become a Data Scientist, and this video helped me a lot to understand what a DS' job entails.
Just a random thought: Lol when you were knocking on her door I was like maybe that’s his sister. But when you guys were in the car and you were thanking her for driving you and she said stfu I was like yep that’s his sister! Lol reminds me so much of me and my brothers! 😂😂😂
I have NO idea. I am a graphic artist. 'ELP.
You're beautiful in ur profile pic
As a person considering a potential career shift into DS-- this is the most inciteful video i have come across. nice work!
You should do a What’s on my Mac Vid to see why you use on your everyday Data Science Apps!!
Data engineering, where muddy waters turn into clear streams of actual data.
This was very helpful. I am in my senior year as a information science major with a concentration in data science/analytics . I’m currently in an internship working with big data, but everything is so confusing when I am trying to understand what I will be doing on an everyday basis in my career. This video has given me A lot of insight 🙏
For someone who knows nothing about computer science, this was absolutely amazingly amazing. Thank you.
First, I would like to thank you for the information. second, I would recommend you to make a series of videos addressing every step of that pyramid and what kind of talent needed/curriculum and maybe even the best place to learn them and the best place to start with. Thanks again.
This blend of information and humor is what the world needs more of 👏
I looped the second minute at least four times to see that dance
Oh man, you help me begin learn what i literally need to know
Most of the videos regarding career guidance are crap on TH-cam.
But this the gem 💎 that is really valuable.
Thank you so much, for this video 🙏❤️
Great editing/content. I would like to know more about how to ask right questions what you do on work