Marina Wyss - Gratitude Driven

Do you want to become a data scientist, but you're feeling overwhelmed with all the skills to learn, how to get experience, and how to set yourself apart in a crowded field? This video is for you! Here I lay out a 12-month roadmap from absolute beginner to your first data science job, even if you're coming from a non-technical background.
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📬 Sign up for my newsletter for access to a FREE 80+ page e-book laying out everything in this video (learning resources, project ideas, LinkedIn checklist, and more):  https://www.gratitudedriven.com/subscribe

💬 If you'd like to chat with me 1:1, you can book a call here: https://topmate.io/marina_wyss

☕ I am really happy to be able to share all of this for free, but if this was helpful and you feel so inclined, you can buy me a coffee here: https://ko-fi.com/marinawyss
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⏰ Timestamps 
00:00 Intro
01:12 Is it even still worth it to become a data scientist?
02:14 How long does it take to become a data scientist?
02:52 Learning timeline
05:59 Choosing a specialization/different kinds of data science roles
09:36 Paths to learning (degrees, bootcamps, self-taught)
10:13 Should you learn math or coding first?
11:59 Should you get certificates for data science?
11:17 Tip on studying with GenAI
11:51 Skills to learn, projects, and learning resources
21:59 You're a data analyst now! Update your resume and start applying to jobs
23:29 More skills to learn, projects, and learning resources
33:10 Skills NOT to learn (at least not yet)
34:24 How to get experience/building a data science portfolio
40:30 Marketing your experience (portfolio, GitHub, LinkedIn, Medium, resumes, cover letters)
44:40 How to get interviews (applying to jobs strategically and networking well)
48:31 How to prepare for interviews
53:31 How to do well in your first job
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🎥 Other videos you might like:
How Over-Preparation Helped Me Succeed in Data Science & ML Interviews
https://www.youtube.com/watch?v=Eo2Z4Lp18gg&t=42s

Study Without Suffering: How to Stay Competitive in Tech (or Any Industry) While Working Full-Time
https://www.youtube.com/watch?v=ZWYc68ejzVc&t=27s

How I 5x'd My Income Working in AI/ML with a Non-Technical Background
https://www.youtube.com/watch?v=6lm8ttDGUMo&t=177s
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✍️ Learning Resources (WAY more in the ebook!)
Practical Statistics for Data Scientists: https://amzn.to/49EqG1A
https://sqlbolt.com/
https://ohmygit.org/
Designing ML Systems: https://amzn.to/3VHeLKU
Stanford ML Specialization: https://imp.i384100.net/9LL6gy
Deep Learning Specialization: https://imp.i384100.net/Xmmz5M

Quick note, many of these links are affiliate links, meaning I'll make a small commission if you purchase them (at no additional cost to you!)
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🦫 About me
I am an Applied Scientist (basically, a blend of Data Scientist/Machine Learning Engineer) at Twitch/Amazon. Outside of my full-time job I'm a technical mentor at a machine learning bootcamp, and a 1:1 career coach for people looking to break into the field, with a focus on those from non-traditional backgrounds. 

I’m also a Certified Personal Trainer, always busy with too many interests, and really, deeply happy with my life. I hope to be able to help others achieve these things, too. 

Instagram:   / gratitudedriven  
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✉️ Contact
Leave me a comment here on YouTube!
Business email: marina@gratitudedriven.com
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⚖️ Disclaimer
The views and opinions expressed in this video are my own and do not reflect the official policy or position of Twitch/Amazon or any other company I have worked for. All advice and insights shared here are based on my personal experiences and should be considered as such.

#datascience #careertransition #datascienceroadmap

Beginner to (Employed) Data Scientist in 2025: Complete Roadmap - Skills, Projects, CV, Interviews

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