How I Would Learn Data Science in 2022 (If I Had to Start Over)

Every year, I like to refresh my advice about how I would go about learning data science from ground zero. The data domain is changing rapidly, and as my own knowledge grows, I think it is important to re-evaluate the approach that I would recommend.

Resources for Learning Data science

Resources for Learning Programming

0:00 Intro
0:42 Is it Possible to Learn Data Science?
1:33 Where to Start Learning
2:33 How to Create a Learning Map
3:55 What Would My Learning Plan Look Like?
5:28 Before You Start with Projects...
7:05 Statistics???
7:45 Project Obsession
9:00 How to Leverage Projects Effectively
10:14 How Long Will This Take?
10:48 An Important Note on Goals

Starting off, I want to debunk the idea that you can “learn data science”. This implies that data science is a static subject that can be learned in its entirety. For better or for worse, data science is constantly evolving and growing. I don’t know a single person including myself, that could possibly know the whole field. Learning data science is a journey not a destination, and coming in with this mindset can make this process far more enjoyable for you.

First, I would start with a learning map. You need to plan your learning journey. Next, I would start learning python. You need to understand the basics here. After that, I highly recommend looking at other peoples projects and work. Finally, focus on data science projects to engrain new topics!


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[KenJee_ds]

(Reminder that all resources I mentioned are linked in the description!)
Thanks for watching everyone! Let me know what your goals for this year are below! Mine Are:
- Do a project with a Generative Adversarial Neural Net
- Enter at least 1 Kaggle Competition
- Do at least 4 projects and share them on YouTube

[ANONIM]

I used your project-based learning approach from last year's video to learn data science. After 15 months and 700 hours of learning (no online courses, just individual studying), I landed as job as a mid-level data scientist in financial fraud detection. Thank you! This video is spot-on. Especially your emphasis of building a roadmap and systematically updating it as you grow.

2 not-obvious study habits which I found helpful:
1. I kept multiple projects open so that after I went through a topic (e.g. feature selection), I could implement it in multiple projects.
2. For each topic in my roadmap, I kept a date of when I last implemented the technique in a project. This helped me identify important topics which I had covered a while ago and might have partially forgotten, so that I could refresh my knowledge/skills.

[vijaykumardobariya]

Path…
1. Coding (Python)/ SQL
2. Do projects on Kaggle
3. Learn Statistics
4. Learn algorithms (classification, regression)
5. Do projects again… (start from interesting projects and goes towards complicated projects )
6. Deep learning (computer vision) >> depends on interest
7. Projects projects projects

[mariopaul]

Been waiting for this video!!!!

To anyone reading this, if you're looking to break into Data Science in 2022 I 100% recommend subscribing to Ken's channel and following his advice!!

Back when COVID-19 started in 2020, I was looking to break into the field and I had no experience, no projects, and I didn't know where to start.

6 MONTHS after subscribing to Ken's channel and soaking in all of his advice through his videos, I got a job as a Data analyst.

I'm living proof that this channel is 100% all that you need to get started. Thank you Ken and & I can't thank you enough for the doors you have opened for me.

[meshiba]

“Learning Data Science is a lifelong journey.”——What a great quote I've heard for today

[LukeBarousse]

I’ve been waiting all year for this! 🙌🏼 Solid advice Ken!

[AhmadBazzi]

Lovely learning map, Ken !
And yes 4:30 math is very important ^^
Love your channel and your content, keep it up.

[miselw]

Thank you for sharing your experience! I just got an internship to be trained as a data analyst and learning Data Science basics. I felt so lost as a person in their mid-thirties feeling like my previous Psychology BS degree with English/Math minor was worthless. Your video has given me hope that I can obtain this knowledge with a bit of planning and goals.

[datalo]

This video is extremely accurate. I have had such a hard time learning how to be a data scientist. I am in a MS in Data Analytics program and feel that doesn't really provide any real direction. I don't know what I don't know and that keeps me from learning what I need to know. Seeing the path helps, thank you. I would like to say I have struggled to learn R and I seem to be getting SQL quickly and I think this will help my confidence. Getting one language down can help to learn another, just from a confidence standpoint.

[achmadrifkiraihansyahbagja]

"When beginning with this projects, they don't have to be original. You can go through the exact same analysis that someone else did, and still learn something. But typical learning session could just be you having someone else's project on half the screen and you typing it line-by-line and running it on other half of the screen. As you do this you can change the parameters, you can experiment with different visuals and see how it works as you go."

This one what i've been thinking for. i feel like i do nothing if i see someone's project and copy it to my notebook, but you just said it and i totally agree. we can experiment it with changing the code, maybe we use a different way to clean the data, or just define a function that others use repeated code, (a.k.a use DRY concept), and so on.

thanks Ken Jee, it really helps me out.

[DataProfessor]

This updated video is epic. Your pioneering "If I had to start over" video had inspired so many similarly named videos in the tech youtube space. Certainly agree with you on the importance of coding and how that opened up several doors of opportunities in accessing "power tools" for the data science learning journey.
8:01 Also thanks for the mention 😆

[mh]

Great advice on typing out other people's work. Myself as a beginner it's easy to get flustered on projects as some solutions/tools I have not yet been exposed to. By looking up other's solutions/work and typing them out it really helps me to understand the anatomy of the code. Furthermore, sometimes the solutions don't work as I am using python 3.10 and so I have to work out and start fishing around for the latest 'iteration' of the module/code and that actually helps to drive home the knowledge.

[iyanuarowosola]

Boss Ken..
6months on the go...
I consider I'm a good learning path.
I'm starting with statistics (19hrs tutorial video), then I will take up math to Excel/python...

Thank you for this

[tokkigifs]

one thing I love about computer science in general is that you don’t stop learning but advancing your skills and knowledge

[waqasali-nwoe]

So I have decided that 2022 will be the best year of my life. I've started learning Python on 1st day of the year and up till now I have covered most of the basics and made some simple programs as well in last 20 days. So far it's going good. Thank you for this video. I wanted to ask, when should I start practicing on Kaggle now? I Study around 1-2 hours daily after my job and 3-4 hours on weekends...

[onishea]

Everytime I watch your videos I feel a little gentle push telling me I can do this and equipping me with all the tools mentally and physically. Thank you Ken. I always have new found confidence and a new way of thinking of things after watching your videos. 😊

[renevanzyl]

Totally new to data science, have not even started learning anything as yet- reason why I watched your video. Ps very enjoyable. Hereafter, I'll remember what you said: write down my goals, but keep evolving them as I learn

[cheekiereynolds]

This has helped me tremendously! I'm a database coordinator and I feel so clueless at times because I don't know enough about this subject. I will definitely take your advice about setting smaller goals. At first, my goal was to take all of these courses, get certified and that would be it. But, now I know that this is a process and learning data science is continuous. I now have a more clearer picture of what my path should look like. Thank you so much! You just gained a sub!

[sunilrskanda]

thank you for Realistic words about learning process Data science.I immense me to follow you day by day for self growth towards Data Science

[joshuaozoya]

Thanks Ken, I took off with python basis last two years, within the space of 2 months, I was already in Pandas, and doing the Jupyter thing. Anyways everything poured on my face, and I just gave up. With this video I saw my mistakes. Roadmap. Starting with the basis and mastering them. Then you proceed. Spend as much time as you want to learn the basis. When your is strong, your building will last forever. Thanks again Ken.

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