The 7 Biggest Data Science Beginner Mistakes 

Thanks for watching everyone! If you're interested in the projects I mentioned in the video they are linked here: Project From Scratch: ru-vid.com/group/PL2zq7klxX5ASFejJj80ob9ZAnBHdz5O1t RU-vid Leaderboard: ru-vid.com/group/PL2zq7klxX5AR8gVxZ-4w1vsVNTO0RDO0_ Ball Classifier: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-vy-R4oUZaC8.html&ab_channel=KenJee Kaggle Projects: ru-vid.com/group/PL2zq7klxX5AQXzNSLtc_LEKFPh2mAvHIO

I wish I saw this at the beginning of my data science journey - could have saved me a lot of headaches and time! Awesome video Ken!!

100% agree on getting your hands dirty early with projects! When I started, I tried various courses and MOOC's but nothing ever stuck. The moment I started attempting my own projects I started to see progress in my learning and I finally started to retain the information I was learning :)

1:53 Wow USB-powered Papayas? Great insights Ken! Yes totally agree with you on the importance of domain knowledge which also helps to differentiate us from others.

HI KEN!! Only two months ago, I started my journey by watching your video(beginner's guide) and today got my first Internship ❤️ thank you for being my ultimate source of motivation!!! Btw Happy Ramadan!! ❤️❤️

Hands-on projects, especially small, focused projects, from the outset will accelerate learning of both the theoretical concepts and the practical skills. For example, learn Python while learning a data acquisition technique provides context and motivation. This approach applies to each stage of the data science workflow and to each of the technologies. Revisit earlier projects and add another stage of the workflow.

Thank you Ken, this video certainly gives me direction and reminder. I love this saying so much, “ Data science isn’t a competition, it’s a long journey of slow and enjoyable progression.” It’s so true!!!

thank you 😊 just started this journey. It has been a month, and loving it already. I know it is going to be tough in upcoming days or months but I am up for it!

It was overwhelmingly scary at the beginning, but now I think I know 'what not to do' if I am to make a path out of my passion for Data. Thank you for coming up with such videos. They are a great help.

Thank you for the tips. I have resonated with the tip on getting involved in projects. I started working on projects recently and there's been immense growth in my understanding of concepts.

Excellent Insights! I totally agree with the point of not applying your knowledge and focusing only on theory as being one of the biggest hurdle for someone new in the field.

As someone who's just starting to learn and explore data science, this is really helpful. Thank you Ken!

Thanks for shedding light on this amazing journey.

Agreed on knowledge of the topic as it helps you understand the data and you have an idea on what to look out for.

Mistake 2 and 4, hit me right in the feels. Definitely guilty of those when I started. Preach Professor Ken, preaaach!!

Love your videos!! As I’m about to graduate with my Masters in a few months, they give me a confidence boost

You are a great mentor, Ken! Thanks for sharing this content as well!

Great video, ken. I found this video very useful as a beginner to data science.

Helpful as always 🙌 Thank you for always guiding beginners like me 🙇🏻‍♂️

Hey Ken just wanted to take the moment to congratulate you for how far you've come. I remember when you were a bit more underground which is just so crazy to think about. I'm super glad to have experienced your growth as your content continues to help me along my own journey, be it about data science/analytics or your philosophies. Anyways, looking forward to more awesome videos and can't wait to someday make it on your podcast!

Yeah, The community helped me to create the learning habit. Thank you so much, Ken.

Bravo, Ken. You´ve certainly figured out a lot of this right. Thanks for sharing!

Hi Ken ! Codebasics channel brought me here. Starting from scratch. 1 month in to learning. Trying to change career. Your channel is amazing. Thanks and please keep posting. Following your projects and works.

getting to see this video at the start of my data science journey ... this is certainly making a lot of sense now

Thank you Ken for sharing your genuine thoughts on this topic. Not gonna lie, I find myself doing some of them too

Fantastically helpful video. Thanks for creating something so uplifting and straightforward! Really excellent reminders and motivation to keep going on my learning path.

I’m a subscriber from South Korea. Your videos always help me to make my decisions when I have complicate thoughts. Thanks for your videos, and I’ll keep enjoying your channel!👍

Thank you very much. I like your honesty.

Thank you for this video. I'll will revisit this video again and again throughout my DS internship this Summer. I've already fell into some of these traps :O

The most refreshing thing about your videos is the honesty. Almost as much as the advise. That and seeing your dad make Cameos 🤣

Great video as always, Ken! & definitely the right choice :D @1:28

Thanks for sharing Ken 👍

Thanks, Ken. Great video.

Thank you Ken ! The fire of obsession and stuck time are strongly correlated negatively for me, but as soon as I take a break and get my ... together I find success in the end. I used to wonder if I really love the field, but after listening to you in this video, I realized that feeling this way should be quite common. I would also add that a big mistake for DS beginners is not watching Ken and Tina's videos :) .. You guys give us all we need to stay on track

Mistake nr 8 : data leakage between your training and testing sets. I saw that being made by an experienced data scientist in my first job. It was ignored and a 85% precision/recall score was announced to management.

Sit thanks.......really from the bottom of my heart thanks....

I almost cried when the video cut over to your introspection clip😂😂😂. Good stuff Ken jee!

I still consider myself a beginner after almost two years of learning. Listen to what he says. He is spot on! I would also add that if TOUS start a MOOC make sure you finish it unless the content seems to advanced for your current level

How I spend my first hour on Saturday mornings. Thanks for the continued motivation and i hope to take your support on here and use it to apply simple ML for my project. 🙂🙏

Thanks for this video, Ken! I'm getting into the part where i am "appllying the theory" in projects and i feel like i've learned nothing at all hahaha It's always good to hear some encouragement from others

"Data science is a marathon and not a sprint"- Nice line ken! Keep going, very helpful video

I've been on my data science journey for a while now and the mistake of neglecting domain knowledge was a big one for me too. Great to see I wasn't the only one :)

Hey one thing I missed: the right learning succession. You need to know your basics and that is calc 1-3 or in Europe mostly analysis 1 and 2. Linear algebra. And from there on stats 1 and 2. And than coding, machine learning and what not. Or regression. But the key is to know your basics. I so often encountered a problem where I missed math knowledge so, people. Learn math and Stats.

Learning data science is like an ML model ... The more you train it the better result you get... Thanks for the tips. At what point one can say or should consider that data science is not for them?

Thumbs up!! just now finished all(all!!) leetcode sql questions!! Looking to finish more questions at another websites

Probably most useful and honest video👍

Excellent suggestions! All of these are very helpful. I do think I am going to go through a project with you so I can start learning. I will let you know which one I start with and how it goes.

I have been working on data analytics projects for 2-3 months now and i have to agree, i am making so many mistakes and so many things are getting lost but the more i work, the more i am learning and the more im practicing and its been a great experience for me honestly. Data analyst/science is probably the most fun job out there and the most challenging one.

Thanks Bro to make me so much clear and i will take care of it.

Thank you for the motivation Kem. I am not the one who is good at maths and statistics . But I love to solve problems in real world . Also somewhere in my mind says data science is good career path for you . So doing it❤️❤️❤️

Thank you Ken.

"Give light and people will find the way" - Ella Baker. Txs Ken.

I hope I learned this early on my early years but I'm still 20 so I have more time to start. thanks for your video, it helped me internalize what you said since Im always burn out before and tried so many stuffs on self dev but the truth is "I have to be honest with myself" and have my own system not copying others. I will become data scientist for next 2-3 years :)

I failed my second course R for the certification of Data Science. Your are right about giving up easily since I am a beginner. I will re-do and study harder. Thank you! Your channel helps me a lot!!

Those are spot on . These are few of the mistake I made when I was starting

Thank you for the video, Ken. I'm just starting to learn about this field and my interest is only increasing. My nowaday's goal is to learn to program in Python.

feeling good after watching this, thank you sir.

You always hear it from seasoned data scientists; just start. But where - right? My advice 1)do small projects. 2)complete a project. 3)literally, rewrite a project you find an example for on RU-vid or a GitHub. Literally, type the solution out word for word. This will allow you to feel the data science flowing through your fingers. Then go back and modify the project you just built. Modify it just enough to change the results. Now you feel the data science even more. Your confidence just went through the roof. Like he said, learn just enough. Cause the reality is that you’ll only use 1/10th of what you learned. At least at the beginning. No one is going to make you a lead out the door. If they do, quit or turn down the job. Also and most important, realize a data scientist in IT is not the same data scientist in Finance. I’m a SQL SME in accounting and finance. but if I hang out with IT SQL SME’s, he’s from mars and I’m from Jupiter. We speak SQL but we use SQL for different goals. Data scientists are the same. Don’t get distracted. You’ll find your place. Just keep DSing.

Thank you!

That video actually came in a good time cause I'm really burning out im my first solo project. Even though I'm not in such a bad position, made a lot of courses and I wrote my first "import pandas as pd" five weeks ago I always feel like I'm having a slower progress than I should. I'll take it easy with myself and start with smaller jobs

I appreciate that you made mention of a community. I am always seeking to assure myself that I am not alone. Is Kaggle the only place that you know of where such a community can be found?

... ''sexy computer vision and deep learning projects '' )))) thanks dude

Point #1 I agree 100%. I'm into sports so learnt quickly that even a bad tennis coach is better than no coach for novices! So I just googled data camp and went for it

great direction

Nice! I feel better now knowing that I ONLY committed 6 out of these 7 mistakes when I first started! #winning

Hey Ken, have you ever thought on making a video on what is important when you are in a data science role already. Would be quite interesting for me to hear your opinion. I sometimes do not know if I should dive VERY deep into some specific topics or just use my freetime to learn something somewhat related. For example I love working with REST Apis and even some Vue Frontend stuff which will not make me a better data scientist, but are also fun... Since I am also a content creator I something think the same way about creating videos. What´s your opinion?

I'd personally recommend watching some free videos on a topic on yt before enrolling in a course. This way you can easier choose a good course because you already know what to look for, and since you already know some basics as you watched that free stuff, the material sinks in better because you are repeating it again while watching the course you chose (plus you get a different angle on the topic). As you say and I can confirm (from a PhD perspective) ;) getting more then one point of view is important. People have a bias and some things are obvious for one person while difficult for another, the choice of words is very important too. Mine main problem is I like theory too much plus I tend to start too many topics at once. I get too impatient and can start NLP topics even though I should be doing e.g. clustering, and NLP is not on the plan for the next few months at least. This has some advantages too (not only bad sides!) - when I get to NLP it's not all new and sinks in better, but me doing that makes the whole process chaotic. Well, I try to pat myself on the back that - in the end - if I fill all the knowledge gaps - it's not that important in what order I did it... Still I know I need more order and systematic approach. And more practice. Other issue with learning DS, or every new thing really, is that you don't know how long it will take you (coz it's new to you and you don't know it so how can you plan how long it will take if you don't even know what are all the things you must learn... if it makes any sense). So - yeah, don't get crazy about deadlines, just focus on the progress. Another pro-tip - browse job offers to see what the companies want. I think this may be area and industry specific - in my area they want people good with databases, Hadoop, Spark and other Big data associated things more then they want Deep Learning & AI specialists. Kinda makes sense when you think of it... So for me, on my road to Data Science, I decided to go back to my analytics job that will let me practice python&SQL more, get my bills payed ;) and practice the DS stuff in my free time (coz I can already see with the Big data things and me still needing to work on my DL skills more this can easily take another 6 months...) So yeah, some comments on Data Science learning from someone who has been learning it for about 6 months ;)

subscribed! for awesome videoss

This video is the best way for a well sleeping for me.

love ur content

Great!

Rip papaya you have , eat it first you must . hahaha. Nice video. I too believe self evaluation is very important before entering in any field. And the field like DS which requires lots and lots of time and learning efforts its crucial to know before you start. Thanks for making people aware of that Ken.

It's a cruel experiment, but there was an experiment on rats in water. It showed that a rat will drown in 15 or so minutes if left unattended, but if you save the rat right as it submerges,, and put it back in the water, it'll keep swimming for another 60+ hours without drowning. It applies to your concept of us always having 100% more to give. In this case it was more than 100% more.

Hi Ken Thanx. me a hard core biologist- of late translational research- fascinated by data science n m encouraged by ur video. look forwrd to train myself. send ya happy thots frm Himalayan foothills India. Stay blessed. 🌸🙏🌸

Thank you for the content! I believe I need to apply the theory to projects more. I haven't yet worked on, let's say, real projects, except for some Kaggle practice and reading. A few days ago, I set out to create a substantial project involving extracting valuable insights from the remote job market, and I'm finding it quite challenging to locate suitable data sources. I mean, I'm investing a lot of time exploring techniques to attempt scraping LinkedIn, for example, but it hasn't been yielding any results so far. I would appreciate any suggestions :)

that 10 minute rule is smart gotta try that

Hey ken please make a video on interview for data science....like what kind of python coding question will be asked, etc...

Hi Ken...thanks for your content. I do a lot of econometrics..learning modelling data (Logit, Ardl, VARs). I think this is a good thing but which skills do i urgently need to learn to call myself a data scientist in your view? Of course divibg deeper into programming etc?

Very informative video. As a IT student myself, I don't know whether I should choose to study data science or network enginner in my next degree course. As I have no experience, idea, knowledge of data science. Do you think it's a great idea to move to data science career or to other IT career? Would appreciate your thoughts on this. Thanks!

I think #3 is person dependent. If you become to reliant on a coach/mentor then your problem is your mentor not coaching you to become a more self-sustainable data scientist. I'd have killed for a bit more guidance in my formative career years rather than go and try lots of solutions. Maybe it's person dependent? Either way, great video. Liked and subscribed!

Unrelated question here!, So Im a junior physics student right now looking to become a data scientist in the future, what is the fastest route to become a data scientist ? Land a data scientist internship, get a data engineering/analyst job, software engineering job, etc? Also I live in San Diego and don't plan on moving is this going to cripple my chances to find work?

Apologies for the unrelated comment but what is the brand-model of the chair that you're using at 4:40? Thank you and more power to you.

Random Q: isnt there a UI (end user stuff) for getting arranging statistics/data instead of doing the hard coding??? (Im guessing all data is in DB SQL like formats so you cant use end user style tools?).

Hi! I like watching your videos. Love and support from India ♥️ There's some thing in particular that I'd like to ask. 1) It's been some time since I completed MySQL course. However i have gone through the videos a few times but still I am not able to gain the confidence of saying that I know SQL. What do you suggest here? 2) Practical knowledge is very important and I am unable to get that. I have a dataset. I make up problem statements in my mind and try solving it. But that is clearly not helping at all. So can you suggest me some places where I can apply the knowledge of Sql that I gained through the course? Course I took: 365 Data Science.

Why does Ken not apply for a Data Scientist job? The job would play much better, wouldn't it ?

So, I am not making most of the beginner mistakes. But I have one question Ken. I don't know enough. Should i see the projects on RU-vid and try to implement them by copying and understanding them? And you told about plagiarism in DS. Will it be like I plagiarized those projects ??

Should I focus more on oop? To be a data scientist

Mistake I personally made, I didn't learn enough math. And I thought that I could brute force my way through a data science course with some hodgepodge math. I think really getting that foundation is pretty important and it can be done in a singular course, it doesn't have to be a year of university math classes

What's the song playing in background?

all is clear thanks but i have one doubt i completed python basics and thinking of data structures (dsa) is dsa needed or required skill for data science or not ? plz reply 🐱

papa jee!! i hope he had a lovely nap :)

Great content as usual! Ken, we know your secret now: Your source of Data Science are Papayas 1:53 :D :D

❤️

hey ken jee, thanks for the info. i am 30 and a total bum. so, i'd like to quit being a bum. this looks like a great career. what do you advise for someone who would like to get started even in something related and not necessarily in it, where from he/she could continue to learn while earning to then move up and /or into this field?

♥️♥️♥️

eh every job is the same basically gets mundane or same same- unless your doing an extreme sport for job...

Hii Ken, right now i am working in data driving company having 1.5 year experience which I have only worked on excel, does this experience will get added to data science and. Yeah is this a right time to take up the course in 365, coz I have been from long time to take up the course

What's with the papaya??🤔

You focus on about DS only u should say something about the person's environment about DS is also affect more than DS itself

I will make sure I don't make these mistakes🤞