Why You Probably Won't Become a Data Scientist
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- čas přidán 15. 07. 2024
- In this video I highlight the main reasons why it is unlikely that you will become a data scientist. TO BE CLEAR I still think it is possible for anyone to break into this field, but I also think it is important to set realistic expectations.
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1) Educational Burden - Data science is a multidisciplinary field. You need to learn computer science, coding, and subject area knowledge. You really need to invest many hours into this endeavor.
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2) Market Saturation - There is a huge supply of entry level data scientists. With more people, that means the probability of landing a data science job is lower.
3) Data Science isn't a good fit for you - It takes a lot of time and dedication to break into this field. It helps to be very passionate about the work. There are other great careers like software engineering that have a lower barrier to entry where you make similar income (if not more).
4) Ambiguity - Data science job postings are very unclear / unreliable.
5) Continued learning - You need to be adaptable in your role. It takes habits or huge motivation to keep studying.
Congratulations! If you made it this far you likely have one of the most important skills for breaking into this field.
That skill is GRIT.
Grit book: amzn.to/3wBez1H
0:00 Intro
0:45 Challenge 1
1:50 Challenge 2
2:55 Challenge 3
3:49 Challenge 4
5:19 Challenge 5
6:10 GOOD NEWS!
7:00 What's Next?
8:22 Blooper
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Thanks for watching everyone! It is an uphill battle, but I still believe that it is possible to make it as a new entrant into this profession! Also, sorry for the self plug, but if you're looking to stay up to date with what I'm reading, learning, etc. I would love it if you signed up for my newsletter! www.kennethjee.com/newsletter
Becoming a software engineer is also very difficult with out a CS degree. You need to learn coding in few languages, oop, design patterns, system design, web tech, and algorithms and data structures. I also find that algorithm & system design interviews are difficult than data science coding interviews.
I am too struggling with keeping up with required skills for DS. The list demanded by employers are getting longer everyday. I think best thing to do is first become a data analyst, it is just like become a front-end developer or programmer in tech. Then gradually build your skills. This way you will also build your network with analyst and data scientist. If you try to learn everything and then attempt to be a data scientist, you will suffer and probably even given up.
Can't believe I've only just stumbled upon your channel. Thanks Ken; love your steez!
Don’t sugarcoat things, Ken. Just tell me I’m not smart enough.
Dude I can't even figure out how react works... Don't think intelligence is the main thing here 😂
Lol , we don't need to smartness we need consistency, And my heart says you are the "Chosen one". 😉
@@KenJee_ds dude I hate css so much I gave up on react
@@prod.kashkari3075 same
@@prod.kashkari3075 "align this box" , oh the text😂
It's can very well be a "who you know" industry as well. (As many are)
A friend of mine got a job as a data scientist because a company didn't really know what a data scientist is capable of, but through conversations with someone at the company, explaining what he's learning and able to do they brought him in on a 6 month contract to test the waters. His work resulted in the company finding inefficiencies in their supply chain that went completely unnoticed for over a decade. Needless to say they offered a full time position and expanded their data analytics/data science department.
This is so true! Great insight James, can't believe I omitted this part!
Despite of all these .. and No matter how many difficulties will come on the way... I'll never give up on becoming data scientist.❤
You got this 💪🏾
Love to hear that Pragati!
@@KenJee_ds 😊✨
Sounds like GRIT to me...👍
Pragati by name pragmati by nature
Thank you for the great video as always Ken. The grit aspect towards the end really speaks to me as someone trying to enter into the field. I remembered when I first started out going into this field my first year at UC Davis, I felt a major hit of imposter syndrome. It all really started out with when I interviewed for a Data Science project for the Data Science club at UC Davis. The president at the time (who interviewed me) asked questions about my project experience, interest in sports (this was a sports analytics project that required computer vision to analyze the movements of players), last book I read, project experience, and my SAT math score. As I answered those questions, he didn't like many answers to any of them (never had projects because I just learned how to code from my Introductory Python course I took the quarter before the interview, not into sports, stupidly said the last book I read was "To Kill a Mockingbird" even though it was a book about Robert Kennedy (I was kind of nervous here), and I scored in the 600 range for math) and proceeded to say this, "Look Jeffrey, I know there's way smarter people than you. Tell me, what makes you stand out?" My response was, "Uh... I'm willing to work," and he said, "*sigh* Everyone's willing to work." I basically failed the interview and he basically implied that this field isn't for me (to add insult to injury, I saw someone do better than me at the interview right after I finished). Not only that, some people thought that I would end up at McDonald's after I graduated. To compensate, I did side projects throughout sophomore year, got accepted into Facebook's Data Science mentorship called the Facebook Data Challenge 2020, secured a summer internship as a Data Analyst at the Federal Reserve Bank of San Francisco, got accepted into the MURPPS Research Program at UC Davis, and I'm on my way to prepare for an interview for a Bioinformatics Research Position in the Molecular and Cell Biology department at UC Davis to use machine learning models to predict the structure of DNA/RNA to determine how this can lead toward genetic diseases. I'm glad that having developed a sense of grit throughout the years has been so far useful for not only proving people wrong, but also giving me great opportunities.
Really inspiring story Jeffrey! Thanks for sharing!! Good luck on your interview!
@@KenJee_ds Thank you! I’m glad that I have made it this far 🙂🙂🙂
noice mate
Wow. Amazing story.
Would love to see a series of tackling struggles like, what method to use and starting processes. Great work!
Thanks for watching Christopher! I have a few videos like that but will try to make some more. You may enjoy these: czcams.com/video/-pdXWmj9xxU/video.html&ab_channel=KenJee czcams.com/video/Uf0dO-pgOrk/video.html&ab_channel=KenJee
3:12 Yes, love for the process is definitely a good reason to become a data scientist. This reminded me of Michael Jordan’s contract including a clause on “For the love of the game” . I am with you on Grit and Persistence as well as patience as the large skill sets that would shape us to become the unique data scientist we would become takes time, care and nurture. As Rome is not built in a day, becoming a data scientist or being a data scientist can take a lifetime to attain or maintain. Thanks Ken for this thought-proving video!
Love this comment data professor! One thing I didn't mention related to passion and "a reason for doing it" friends with similar interests help to motivate as well. You've definitely been one of those for me on this CZcams journey!
@@KenJee_ds Wow, very honored and likewise, I am always inspired by your content and your innovation in this space. I definitely agree with you on this, the journey is very much enjoyable when you have friends with you. Thanks!
I have graduated in civil engineering.... But I wanted to be a data scientist... I have picked up a online course from coursera powered by IBM.... & I do follow you as well so that I can get more knowledge.... One day I will be a successful data scientist... ❤️
That's the spirit!
I just graduated from Manufacturing Engineering and currently starting out as a data analyst while self studying and taking online courses to be ready to transition to data science one day. We got this!
@@mjsantos8492 yup!
Hey there, how’s your progress so far ? I’m a civil engineer by myself too and currently using Udemy ds course and other free resources to learn
@@the12345a1 well, by now I am learning machine learning and it needs more maths.... Soon i will start to do projects may be 1 or 2
Great advice, Ken. As someone trying to break into the field from a MS Math, I agree the entry level market is oversaturated, though a lot of candidates are unqualified. MSDS programs (which seem to dictate which skills are "trending") put emphasis on data viz & ML in Python (pandas, NumPy, Matplotlib, scikit-learn) but from what I've seen in job postings, very few data roles use these. Outside of FAANG, where ML operations are critical, most companies need analysts (SQL, Tableau) or SWEs to build pipelines. Creating Jupyter notebooks and applying scikit-learn is a very narrow, high-supply-low-demand skillset. There is a 2020 MIT article suggesting 1 in 10 companies benefited from ML efforts.
I think it's important to learn skills that are trending once you're in the field, but until then it's better to learn skills that are in high demand (SQL, Tableau, cloud services). This is what I'm dedicating my time to now.
Thanks for watching and I appreciate the detailed comment Tyson! Would love to see that article if you don't mind forwarding it along!
@@KenJee_ds I'm not sure if CZcams deleted my comment for having a link or what, but I'll repost just the article title. It's called "Expanding AI's Impact With Organizational Learning". It's partially behind a paywall so I'd only take it with a grain of salt, but the authors do seem credible.
@@tysonpond7755 Great, thanks! It may have just gone to the warning folder
I disagree. I started working as a data scientist 5 years ago with my undergraduate in Mathematics. The people who picked up the role more quickly were actually the CS majors. The DS MS I'm almost finished with now focuses too much on the analytics/visualization aspect and not enough on building ML from scratch. If you want to make actual good money as a DS, you need to be strong computationally and be able to develop your own optimized models. The SAS job openings pay like 50-100+k less than the true ML DS jobs and should probably be labeled "data analyst"
I honestly came here because I just started learning about data science and was considering it as a career opportunity, and this video was great for helping me not only feel informed on how much education is needed but also that the market is SATURATED. I'm leaving a saturated job market, so that's really important to me! Thank you!!!
Happy to hear this helped!! Thanks for watching!
and then after you became a data scientist, you will realize that after all, its just a statistics with extra software engineering skills. Too many people get stucked in a cool complex algorithm trap while the most important thing in becoming a data scientist (unless you work in a really specific field like NLP & Computer Vision), is to have a solid statistics base
I agree!
I agree. I just graduated with a BS in Data Analytics- I came from the background of zero programming knowledge. The beginning part of understanding the concept, syntax of these programs were extremely difficult and questioned myself a few times. But through many hours of study and self motivation, I began getting a comfortable understanding to the logic and usage of these different tools. I now feel confident using and explaining data science, and now thinking of pursuing my graduate degree in DS. I want to tell anyone reading this. Keep pushing and pushing, you to can learn data analytics, but like ken said, you have to have the grit and willingness to push through adversity and ambiguity.
I hope I am able to land a job soon as a data analyst. Good luck to all!
Amazing! good luck on your job search!
Thanks for the video Ken. I've just started studying a data science certificate and am absolutely struggling. I'm just say "grit and determination" to myself over and over!
You can do it! It was hard for me too, and I made it!
Thanks for being sincere about this kind of journey. Lets make our best effort and never give up. Greetings from Argentina!
Thanks for watching Joel! Let's make our best effort for sure!
Appreciate this Ken, I watched this to really test my mettle before embarking on my masters in data science and AI because it was on my recommended list. Safe to say I paid attention to the points you made but I didn’t feel disheartened at any point! Thanks for this video and pointing out the challenges faced, I think it’s very important to be aware of these challenges beforehand.
Glad to hear!! Good luck with your masters!
Hey dude how is it to be balancing data science and ai?
@@pravanw.5365 I am yet to start, which will be in September. In terms of balancing the two from the prelim research I’ve been doing over summer the fields are intertwined and mesh together fairly well. Maybe I would advise that starting early and really devoting yourself to the craft is the way forward, be worth it in the end.
@@Phoenix-sh8vg thanks mate for the reply.. one question if you dont mind me asking.. does your masters have the same amount of content in AI as a usual AI masters or is it less to give time for the data science part?
@@pravanw.5365 My apologies only just saw this, I believe it’s largely a splyce of the two, as I am learning modules such as data mining and I chose optional modules such as Bio optimisation which is quite AI heavy.
Great video mate. I am currently completing a MSc in Data science (4 courses done). While I am loving the learning process and fascinated by the field, I have no current plans to have a career in Data science. I get way too caught up when working on a project (especially when debugging code) that other aspects of my life and frankly sanity, suffer. So I can't imagine doing that for a living, as I will never disconnect enough from work.
Thanks for watching Kenny! I think that having the data science skillset can make you more effective in many other types of work! I think it is awesome that you are learning about it though!
Great video Ken!
I feel you, I cried two days ago trying to fit data into SVM and Adaboost.
The first worked, but the second still doesn't. Gotta keep on grinding, eh?!
keep grinding!!! I've cried far more than I would like to admit about the profession (not from eating hot peppers)
Been watching hours of your material (and Tina) because while I do know that it is not an easy field, I’ve been fascinated by it ever since I first found out about it. Data Analysis is my passion and the one thing I feel I came to the world for, and this role I feel like it’s the pinnacle of it. I will not give up.
Awesome!! You can do it, I'm sure its not just blind ambition (couldn't help but make a joke on your name)
Hahahaha my senses all tell me it’s the right thing 😉
Passion is definitely what pushed me through! Don't think there's anyway around that, if you don't have it you will burn out
Agreed!! Burnout is real!
I am still at uni (bs comp sci) making a career pivot, and I must say I was hesitant to watch this video (scared the title would be true)…
Anyway, I watched it. Loved it.
I still love data, and learning (even though the uni mountain seems HUGE sometimes) and you didn’t scare me off.
I will get there.
Keep up the good work, love the videos and the newsletter!! Oh, that blooper was gold 🤣
Glad to hear you loved the video! Thanks for watching my videos :)
True indeed, I have worked as a data scientist for 2 years shifted my focus from data engineering to data science and after 2.5 years took a complete U-TURN and currently settled with ML/Data engineer. One thing I enjoyed working with DS is to get a complete understanding of maths behind numerical computing library such as TensorFlow, which was quite rewarding for me.
Although during the journey, I realized that I always want to be an engineer and moreover there is more opportunity as an Engineer rather than being a data scientist.
Thanks for watching! Really cool to see that you were introspective about your work and were able to move towards a role that matched you best!
Wow, thanks for the video, and I'm just switching over my career now and I'm really concerned, I feel old because I just a starter programmer and trying to learn data science from zero. And now I just don't know what to say, I guess I don't have any possible way to not continued to pursue this career. There is something amazing and special about this. Something from the core from the foundation that I want to learn, to know, and master. The problem is that none of us are immortals. But I will continue to persist, thanks again for sharing...
Really glad to hear the video helped Eduardo! Keep your chin up!
Great video with great, useful information. Thank you.
Thanks for watching Michael!
Recently finished listening to the audio book of Grit - strongly recommend this book for anyone also curious about cases demonstrating principles you can apply to measure/hone/learn about achievement via a quantitative social sciences lens.
Yes!
I think #3 is by far the most important. It's pretty easy to get sucked in because everybody else is. Maybe this is not for you though and that's okay! You're not a failure for realizing that and going after something else.
I agree!! I didn't put it at the end because I wanted everyone to see that one haha
Thanks Ken!
I'm a college student in my freshman year and wanted to be a data scientist too.
Everyday I spend hours of learning code and math. Like what you've told us, it really consuming my energy and time at the point where I don't spend a lot of time with people around me. Kinda hard to find balance but I really enjoy what I'm doing and preparation for coming years.
It also hard to find balance between data science or my college, before I came into this, I was straight A students but this semester I'm not sure because I spend too much time for learn data science.
Btw thanks for the insights!
Thanks for watching Dylan! I think learning the skills is a good idea, but I would focus as much time and effort as you can on internships! You learn a lot on the job, and these will do even more for you in the job market than straight a's! Definitely give yourself a break sometimes though!
thank you! I'll look for some internship later
My personal advice is to start as a Data Analyst (or Business Analyst), study on your free time and kick ass on your job. If you're open to your boss and he/she likes you, it will be much easier to make an internal transition to ds inside the company you already work for. It's not still not easy tho.. good luck!
Completely agree!!!
i also climbed the analyst stack:
analyst -> statistician -> data science
even when u get to data scientist, you'll want to be a ML engineer, or a cloud engineer supporting ai applications
their is no bottom to how deep technical skills go
I am a BA and looking for transition into Web app development. But DS also interests me a lot. In your opinion what would be the best path ?
I think consistency is the most important thing I learned this year, with channels such as yours and with challenges such as #66daysofdata and #100DaysOfCode. Specially since my college classes are not tech related, since I study political science, but I want to incorporate data science tools into political analysis, so having a schedule of 1h of learning and coding everyday is helping so much! I might not become a data scientist per se, but I really believe that with consistency and perseverance I will be able to learn the skills by the end of the year! 😁
Really happy to hear the challenges were helpful Amanda!! I think that data literacy is going to be even more important in politics in the future. Looking forward to seeing you lead that revolution!
@@KenJee_ds Thanks Ken! 😁
You are amazing and inspiring. Much love.
Thanks Amir!
New look I see💯
I think for me it time management with college and data science and Internship going on hard to handle and also take care of my personal needs etc is hard but putting in efforts also loved your point and reality check this willl help us to make some relatistc expectations and also have backup and be ready adjust a but when time comes 💯🙌
Time management is tough when you have to learn new skills, I feel this too specially since my college classes are not tech related.
Yes, time management can be very difficult! I will say that it is important to look at data science and learning in general as a marathon not a sprint. You can balance learning / school etc. over the long haul rather than equally right now. For example while doing your internship, you probably don't need to do as much (if any) outside data science study. I hope this helps shruti!
@@KenJee_ds yes it does
Thank you Ken 💯🙌
Being in software engineering for 30 years, having built tooling to do data cleaning , ingest, data management etc there is wide breath and depth one needs to have in their tool box dependent on the size of the company your apply too, which many don’t grasp, it not all just stats and charts
Completely agree!
I have no experience in anything. Graduated with a 2.5 in college. Just go admitted to grad school in data science! You could do it too!
Congrats Chris!!
Congratulations ! Would you please which school ? I’m looking for master in data science too. Thanks
Brutally Honest video. Brutal but Honest. Thanks Ken for showing the reality . However I will still follow this path. When I started this journey I promised myself that I will do whatever it takes.
Glad to hear Piyush! I can tell you're dedicated!
I appreciate the thoughts ken as its 100% truth of the current market situation and no sugar coating.
Thanks for watching Abhilash!!
I know it'll be really hard, I know that there are a lot of obstacles, but I'll try my best and become better every single day to reach my goal. :)
Really glad to hear! Thanks for tuning into the video!
Thank you for this video Ken Jee
Thanks for watching Aditya!
In a nutshell, DS is hard to learn and put in practice because it requires a lot of passion to learn a lot of topics from different fields, and obviously there's is not a roadmap to learn all these skills.
Imagine that you are living as an architect in the earlies of the industrial revolution, then suddenly there's a boom for mechanical engineering with not structure at all to learn all the stuff. You'll have to learn by yourself physics, math, thermodynamics, etc. This is how DS is, is a new field and a lot of information to drive someone crazy.
Great analogy Alejandro!
I love to learn and my friends say I have a thirst for knowledge. Some odd reason lol I kinda like the data cleaning aspect. Honestly I want to learn data science to align with my life purpose
That is awesome! Honestly, if you love the cleaning process, you may want to first look into data engineering. That is the fastest growing part of the data science domain and a lot of opportunity there!
I was getting my Azure Certifications and ran across the data related certifications. It just sort of made sense and next thing I knew I was taking a Data Science class with Johns Hopkins and tearing through it. I had already taken a class on RStudio so a good bit of it transferred over nicely. Data Science and Data Analyst were both fascinating fields.
Glad you like the domain! It sounds like you have a passion for it which is super important in my opinion
I suppose the first challenge is the most obvious especially in a bank I work for. All dudes are at least holders of Masters in Maths or CS etc. In my current position I work within members of this team and they're all very good in DS.
Great video. I've been following this channel it's been a while. I'm at a tough crossroad now.
My current field is Industrial Engineering (machinery maintenance). I want to switch to Data Science so I can make use of my academic knowledge to the full (Maths and Programming), also because I think DS is more Future Proof. I couldn't reach a firm decision yet, still hesitant.
People who made a career shift to DS, what are your thought on this?
Thanks for watching Anthony! I don't think you have to make a full "Jump" at any time. You can continue to aggregate the skills, do projects, etc. over time. You may find a role in the future that combines IE and data science that would be a perfect fit. I would look at it less of a crossroads and more of a slow transition gradient. I hope this helps!
hey Ken, greetings of the day...I was wondering if you can make a video about creating a data science startup...thanks in advance
I would love to do that! I don't have much experience with it, so may bring someone else on the podcast to talk about it. I've already talked with two people who have data science startups on the show if those would be interesting: czcams.com/video/Ycf45olhAGo/video.html&ab_channel=Ken%27sNearestNeighborsPodcast
czcams.com/video/7VcdvSyoxnc/video.html&ab_channel=KenJee
7:42 Ohhh my... I was dying laughing at this one 😂😂. Unfortunately, because I can totally relate 😫.
Loved this vid Ken, great perspective as usual!!
Thanks Luke!! Yes, plenty of tears from data science and hot peppers!
Hey, It is good to know the challenges you will face in achieving a particular thing. Thanks for that... 66daysofdata data helping me to nurture the good habit of data science learning. I will try my best to achieve my goal...
💪
8:24 Wait, what? Haha, that was a hilarious blooper!
Lool!!
The bloopers are rarely funny, but I figured I had to do something with that one haha
Lmaoo😂
Hi! Would you mind sharing how you got into data science? As in what was your path to this career and what you suggest for someone still deciding where to go to college.
I made this video on the topic! czcams.com/video/n3vw0M5RrPU/video.html&ab_channel=KenJee
I also made this video for college students which I think may help! czcams.com/video/xjhW1rSQeik/video.html&ab_channel=KenJee
"Great data sex"
Wow, I finally know the words to describe the fun week I've spent cleaning and fixing the data for one of the projects at job xD
hahaha feel free to make a meme about it 😂
this just motivated me more.
Great to hear Daryl!
That wink was so cute. I started reading GRIT a week ago, it’s a good book.
Haha thanks! I was clearly a huge fan of it!
Yes, I whole heartily agree with you that education is a important requirement. I would be careful in putting "Barrier to Entry" and "Education" in the same sentence. A lack of education is a barrier to achieve one's potential. Also you need to apply what you learn and not let it perish or atrophy over time. I have copied code that I didn't fully understand and got it work. I believe that there are amatuer data scientists out there that one day could turn professional.
Good points!
I’m pursuing my masters in data science and analytics this fall, focused on human centered design.
That sounds like an awesome program!
I know it is not easy to break into this field but I won't easily give up. I hope I can become a data scientist.
That's the spirit!
Thank you, couldn't put my experience in better words
Really glad to hear this matched up with your experience! Thank you for watching!
I will become a data scientist for sure!! With one course on Udemy I figured out to clear up my basics and going on continued with the journey for the basics. Will learn it at any cost !! ❤️❤️
Great stuff Dhruv!
Udemy me free course h ya paid?
LOL'ed at the goofy giggle to "data-sex" at the end.
One of the few bloopers I kept in haha
I appreciate the resources. Very helpful. Just wondering if there’s any discount for upgrading “interview query”? Thanks 👍
Currently working on this! Hoping to get one in the next few weeks. I will share it on my newsletter when it comes through!
@@KenJee_ds Looking forward to it. I have subscribed the newsletter. It’s great👍
I’m a seasoned data analyst and can say the following. The big data domain, so that’s data science (aka machine learning), data analytics and business intelligence, are tech fields, but not colourful ones. The focus is business strategy from a data-driven perspective. You do not deliver products as you will not be building or designing applications. You deliver insights, and in time this will have an impact on the business. So no fast/direct impact. Very high-level. You need to like thinking long-term about the business. So no colour, no app building, no designing. It’s all about strategy. You are not a developer; you are a strategist. So if you see yourself doing that, go for it. If you see yourself building or designing, don’t go for it and go for development/designing jobs. Now, there actually is a development type of job in the big data domain: data engineering. But that’s boring and really the data preparation work that nobody wants to do. They just prepare the data for the analysts to analyse. That’s it. I’m sorry for all the data engineers reading this, but it’s the truth and you know it. But hey, if you have a passion for that, go for it what can I say.
So this sums it up. Good luck 👍🏻
Just a couple of comments on this excellent video:
For Challenge 4: Actually I'd said find the COMPANIES you'd like to go in order to decide what you want to learn. Try to learn as much as you can from them, and not just their recruitment process. Now, I have yet to find a data science job but I've been around in the job hunting department. There's nothing that puts off an employer more than someone in an interview knowing nothing about the company (I've been there!) ... the reverse is also true, there's nothing more compelling for a prospective employer than an canditate who not just put out the work on their skills but on knowing the company (i've been there too!). It show commitment and the right kind too!
As for the continued learning part, I've learned (duh!) that it something that you need to do constantly for a good life anyways ... no matter what job or hobby you like to do. I probably cited the following quotes a 1000 times in my entourage and probably here too but listen (possibly again):
"We are what we repeatedly do. Excellence then is not an act but an habit!". You'll find out that this quote holds true not just for data science but also ... anything really in life really.
It is also why challenge like #66daysofdata are valuable ... and not just for you professional career but, again ... for anything you want to do really.
There is a metric tons of things to say about habit formation and, again, I still stand by the methods of stephen guise (which really work well!), but the gist of it is actually quite simple:
work on making your habit sustainable long term before trying to put in massive loads of work. if you do the latter, chances are high you'll burn out (fast!). Do the former, and your brain and body will slowly adjust and adapt to that new habit you're trying to form.
PS: The variance is quite around the 66 mean to form a new habit. Some can take almost 215 days to form and others can take hold in as little as 12 days!! (I've been there on both front!)
But, as they say, your mileage may vary!!
Safe journey and good luck everyone :o)
Oh and by the way, about the sweat and tears thingy ... is that where expression like "Python's zen" are coming from? I do VIVIDLY remember in the beginning that I almost become one of those people who ... you know ... "explain vigourously" to their computer and code that they should have cooperated (and by that I mean smashing the whole thing down).
Makes someone wonder if that's where the python's zen is coming from hum ...
Completely agree about doing your homework for the company!! THanks for the detailed info!
Thanks for the tips. I am interested in data analysis for public health care. I am a public health physician currently working in the field of HIV/AIDS. I would be delighted to get ideas on how to start a career in data analysis. I am presently learning excel but don't know the areas to focus on. I also need to join online communities of public health data analysts.
kaggle.com is one of the best places to start in my opinion
“Data Science is the Frankentein of Computer Science with Statistics and Business knowledge”-How a quote can be funny and meaningful at the same time..haha
Haha yes!
@@KenJee_ds is it worth to switch from software developer to data science?
Done Voting for you !!! 🙌🙌
Thanks!
06:26 was that a wink? 🤣
I hope it was😂🙌
Lol I just went to it 🤣 funny stuff
@@BoitumeloMasekoM that chuckle at the end was like: “That was a fail but I am going with it...”
That was like "Death Wink" from One Piece :3
@@Ibraheem_ElAnsari Ken is THAT powerful 💪🏻
I have been working a full time job and doing a data science diploma simultaneously but its really difficult. I still get stunned by the huge potential analysis have on every industry but being a biologist by my degree and clinical researcher by my job, coding sometimes really feels like an impossible task.
I fear I might not be able to succeed in this huge jump from one industry to another but I am hopeful.
1. How do I learn the syntax? I understand the logic but whenever I try doing something, I am unable to recall the correct syntax.
2. How do I overcome the fear of losing this epic jump? I love data and I am trying my level best to work on it but sometimes I just feel very low and don't feel like continuing because of my hectic schedule.
Thanks for watching! To answer your questions: 1) I recommend coding a LOT. Honestly though, syntax doesn't matter much. I google the stupidest stuff sometimes. The more you do it the more intuition you build around it. 2) The fear never goes away, I recommend building a portfolio so that you can show yourself how what you can / have built over time. If you can build it once you can pick it up and build it or something else again! I hope this helps!
@@KenJee_ds thank you! Your videos and advices always keeps me motivated 🌟
Ken, are you planning to upload any youtube short videos about data science?
I did one that didn't have much success. What type of content would you like to see for those?
@@KenJee_ds such as statistics tips and tricks or python tips and tricks about data science would be good actually. Explaining what some tools do can be helpful as well.
The odds are surely stacked against me being 46 years of age and only having worked jobs that pay minimum wage or $1 above minimum wage at most, and no related job experience. Yet, I still refuse to give up on the good life even if it means settling to be a data analyst or some other computer science job like software engineering, data engineering, DBA, etc. If I want the good life, quitting is not an option.
Just break in to tech and then move from there. Data analyst is probably a great profession.. the title just isn't as sexy.
That is the right attitude to have! It is totally ok to start with a data analyst or swe role and move into data science from there. You could look at it like a stepping stone! If I had to go back, that is likely how I would do it!
@@MichaelImo A data analyst role would seem pretty sexy to me compared to all the civilian jobs I've ever held.
Where do you think the ML engineering field is heading? Saturation the same ?
I think that it the skillset for MLE is perhaps a bit more specific than that of a data scientist. It will probably start to saturate more over time, but companies are constantly scrambling to find people who have the MLE skillset these days!
So I’m studying management data analysis, would that be in data science role or data analytic?
Really depends on the specific program! Probably more related to data analytics though
Hi, thank you for this great advice! I really wanted to become a data scientist but now I've been considering that choice for a while.. Is it possible for me to take a master degree in data science after a bachelor degree in actuarial science?
Thanks for watching!! Yes, it is possible to do that!
That corny wink about the email was awesome. Love the video Ken. Now I can go back to making snarky comments about it on LinkedIn...
Haha I hope you signed up 😉
@@KenJee_ds of course I did!
Cannot find the discord channel as i've heard in 2 different videos about it kindly share it.
Sorry about that! discord.gg/BRv6YGb
Today I asked my professor why he's doing PhD in S. E rather then Ds and he said ds is a technique not a field but due to its popularity its a field now and its a very small part of S.E and mostly apply rules of S. E
"Continued learning" and "Grit". I need to continue learning about how to have the "Continued learning" skill set.
The book grit was awesome for that!
I find it so interesting how just 4-5 years ago, all you heard was how this career was booming, when in reality its overly saturated, especially with people who have years of experience over a recent college graduate. Saying that, I say keep striving for it if you want it. Just dont think its a freebe. Grind out and good luck out there!
I think that only some levels of the career are well saturated. At a mid level ds role there is actually a huge shortage of talent. If you can stick in it long enough to get there, there is a ton of opportunity!
Hi Ken, is data science suitable for introverts?
Can you make a video on what college courses I should take in order to get into data science
I can look into it! Honestly, I recommend taking some basic python programming, statistics, calc, linear algebra, and maybe a algorithms class. The rest is learning through projects
Hi Ken Jee
I want to ask, what do you think of CS50 Introduction to programming offered by Harvard? I am an absolute beginner, started learning python few days ago. The course offers other additional programming languages like Java, C, SQL etc. So shall I go for it? Or will there be extra unnecessary knowledge that has nothing to do with data science?
I think it is a great introduction to computer science, but a kinda bad intro to programming. I would focus your time more on python specific programming courses for pure function. It could be good to complement that to give you a bit broader understanding if you want. I didn't find it to have much application for data science in general
@@KenJee_ds
Your reply was so helpful, thank you!
I'm still trying to find my own path, do you think data science is a good option or should I opt for something else?
I think it is worth learning more about. If you find that you like it after experimenting a bit it could definitely be worth pursuing .
Very insightful and sad reality
Passion is needed to shine in any field
💪
I was interested in this field as an entrepreneur, either way guaranteed income... but my real passion is aquaculture
bio-engineering thus in itself is a multi disciplinary beast, interesting info
Thanks for watching!
Might consider learning UX no code writing
Front-end and back-end was just too brutal
Not a bad route either!
I will be graduating in December (Ph.D. Chemistry). I am interested in getting into Data Science. Have you got any good starting point and tips for me? I got a bit worried watching your video there 😅
Sorry for the late reply Tejas! I answered your other question, but projects that showcase your skills are always top priority for me!
@@KenJee_ds Thanks! Cheers 😀
DS will probably eventually just be broken apart. Data engineers, ML engineers, DAs, etc. I like the tech side of it personally so I’m leaning more towards engineering and analysis. But that’s just my preference. It can be hard to break into “data science”. So I’d tell people to not get so hung up on the title. When I finished my internship I had an offer for a data scientist role and a data analyst role. The DA role played nearly twice as much and used much of the same tech. Keep your options open.
I agree - I think a lot of industries are generating a lot of data and to have some data analysis skills is quite valuable whatever job you have. You can then use a combination of analysis and optimisation to improve our output. At least that is what I am trying to do as a Mechanical Engineer 💪
I also agree! I think ambiguity in the positions is one of these that irks me the most. It is a vast inefficiency in the market that should eventually correct!
I got lucky and in early since I studied stats like 15 years ago and did lots of programming projects on the side. Just sort of feel into it... These days I wouldn't aim for being a ds but instead data engineering or BI / analyst stuff. Go in through the back door
I tend to agree! There is always less of a line to the back door!
This is probably the tip I needed to hear
Fight to the finish! :)
💪
I cannot agree enough about the point he makes where people don't understand the job. So many people want to skip over the data cleansing portion and get straight to modeling. These people tend to lack the CS skills required for data cleaning too. Data cleansing is the majority of the job and it's disappointing to see the lack of skills in this area among my peers.
Doing my best to set some clear expectations haha. I think one of the biggest problems in the field is that there are few people talking about what the actual work is like.
@@KenJee_ds I couldn’t agree more. Keep up the great work!
Ken between Data Science and Data Analytics wich one is more compatible with getting a remote job from another country? Keep it up man
Good question! I honestly would say they are about equal in probability of landing a position remote. The percent of data science jobs that can be done remote is higher, but the number of total data analyst positions is greater, so I think it should even out! Thanks for watching Christian!
@@KenJee_ds great answer thank you 👍🏼
It's been a tough journey for me till date.. Learnt a lot but still lot to learn.. DS is not a easy field to pursue..
It can be very tough but is rewarding!
@@KenJee_ds I love the subject a lot (all those concepts and theories) but I find it difficult while applying it- the coding part... Trying a lot but not finding the right way as far as coding is concerned, especially Python.. Suggestions please..
0:40-Education Barrier
2:16-
I just created Resume and currently preparing for Interview. And I don't have any degree. I don't have anything that is good related to Education to put on Resume. Everything relevant for Data Science I Learnt by myself. In few days I'll start applying. Don't know what will happen Since I don't have a degree
Good luck Krishna! I'm interested to hear how it goes as well. I think that you may have more success on non-traditional channels like linkedin, cold email, or with sharing any projects you work on. I hope this advice helps!
@@KenJee_ds Thank You :)
How can you fare as a freelance data scientist or a machine learning engineer?
It is definitely possible to make a living doing that. I would check out this podcast episode about it: czcams.com/video/DjFi2DOnud0/video.html&ab_channel=Ken%27sNearestNeighborsPodcast.
The big thing there is just having proof of work (either projects or previous contracts)
Link to the discord?
Thank you so much for your content, it is super helpful! Would you say the educational barrier in this field is something that matters long-term? I completed an MA program in Social Sciences and I am continuing to improve my technical skills but I'm scared of not being taken seriously because I don't have a STEM degree.
I think a strong portfolio outweighs a stem degree. Usually employers are looking to just check a box if you're technical enough. If you can show it in a portfolio that is usually enough!
When did you find out you really like data science? I assume you took some general CS classes and they teach you about technicality of what you do as a data scientist? But correct me if I am wrong. I want to know if I would like data science or not but I am not sure how I can do that. I would really appreciate it a lot if you could help me.
I fell in love with data science before I learned what it was honestly. I started trying to predict sports scores early on, and I would do anything I could to make my predictions more accurate. I fell in love with building models to do this. I later found out that what I was doing was some version of data science. I personally recommend finding a problem you want to solve or learn more about, and try to solve it with some data science tools. If you don't like that process of struggling through a problem, data science may not be super enjoyable (you still struggle through problems late in your career)
@@KenJee_ds I always wondered if some numbers lotteries pulls show up more than others even though I have never bought a lottery ticket in my life 😂 I would love to see it using data science and if I want to do or learn something and there is a problem I can spend half my day straight up trying to solve it forgetting to eat so perhaps I might like this field. Thank you for the answer by the way.
@@butWhyDad Sounds like it could be a good fit!
I got a data scientist job right out of college. To be far I graduated with a computer science degree with a minior in mathematics.
Awesome! That is a really strong background to come from
I got my first data science job, and I start on 8-6-2021!
Congrats!!!!
The blooper at the end is the quality content I subscribed for.
Thanks for watching Richard! I couldn't just let that one go unappreciated 😂
is this the same as a data analyst, if not would you say they have the same or similar barrier to entry?
Barrier of entry for data analyst is definitely lower! I recommend landing a job there and then transitioning!
A classic marketing, they show you your weakness and your barrier to make sure you feel scare. Then, they sell their product or promote their youtube video to get more adsense
Hey, I have a finance and accounting background, if I learn python,R and different languages and technical things related to data science, with relevant solo and open source projects, with relevant internships, can I get a good job in the field?
I think it is definitely possible!
Hi. I did accounting as well, I spent 1 year in EY until I found myself not really enjoying it. So I took Coursera machine learning course and join in a Kaggle beginner competition. Yet still hard to get the very first job as a data analyst. I guess that a good project experience is vital for entering the field if your background is not Data Science/Computer Science.
@@yuejiang5759 I think a commerce background can only fetch us analyst positions, because the big companies probably don't trust non-technical background candidates enough for a data scientist position
@@nopenopenopington Yup, after a few years of experience as an analyst it could be possible to switch to a data scientist position.
Is it unwise for someone who studied electrical engineering to master in data science?
I think it really depends on the career outcomes you want. I don't think it would be a stretch to make that transition