Tech resources I WISH I knew earlier

@vinnysaucee

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Promoted product

5-page guide on learning the math behind AI/ML

Why it worked

The video provides high-value, actionable educational content that solves a specific pain point for a niche audience, using a lead magnet to drive high comment engagement.

Summary

The creator shares a list of free educational resources for learning the mathematics required for AI and machine learning careers. He offers a 5-page guide to viewers who comment a specific keyword on the video.

Structure

1Identify the problem of learning math for AI
2List specific free online resources
3Explain the value of each resource
4Present the lead magnet offer
5Call to action for engagement

Product placement

The creator promotes his own 5-page guide as a lead magnet to build an email list or engagement.

Call to action

Follow + comment “roadmap” for a 5-page guide on how to learn the math behind AI/ML

On-screen text

AI/ML - Math edition Tech resources I WISH I knew earlier Freshman year AI internship @ FAANG 20 second guide to become a master at AI/ML 1) Khan Academy Linear Algebra 2) mathisfun.com and xaktly.math 3) MIT stats and prob free course 4) Visualize with seeing theory 4) Visualize with 3Blue1Brown 5) Practice AI/ML projects with this e-book Follow + comment “roadmap” for a 5-page guide on how to learn the math behind AI/ML

Original caption

follow + comment “roadmap” for a 5-page guide on learning the math behind AI/ML/datascience. #cs #learn #ai #datascience #math

More from @vinnysaucee

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Transcript

If you suck at math just like me, but you're trying to break into AI, machine learning, or data science, here's exactly how I relearned the fundamentals to land top AI roles. So listen up for the next 20 seconds because I'm going to show you a free roadmap that will change your perspective on math. If I were you, I'd start by learning linear algebra on Khan Academy. Then I'd fill in my knowledge gaps with mathisfun.com and xaktly.math. This free MIT course helped me self-learn statistics and probability. And if you're struggling to visualize any of this, I'd use this site called Seeing Theory. And I'd also use 3Blue1Brown videos. Lastly, this underground free ebook really tied everything together and made things so much easier. Follow and comment roadmap for a 5-page guide on how to learn the math behind AI/ML. So comment roadmap and I'll send this ebook along with the other resources. Good luck and I'll see you tomorrow.