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

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

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Beginner to (Employed) Data Scientist in 2025: Complete Roadmap - Skills, Projects, CV, Interviews
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. ---------------------------------------- 📬 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 ---------------------------------------- ⏰ 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 ---------------------------------------- 🎥 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 ---------------------------------------- ✍️ 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!) ---------------------------------------- 🦫 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 ---------------------------------------- ✉️ Contact Leave me a comment here on YouTube! Business email: [email protected] ---------------------------------------- ⚖️ 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