Check out HubSpot's AI Adoption Playbook - https://clickhubspot.com/e0e4c3

In this video, I've talked in detail about all the different concepts you need to learn to become an AI Engineer. 

I've shared important resources and tips that will help you get started in your journey of learning AI.

AI is a fascinating field, and if you can invest just one hour every day for 90 days, you will be able to build your own custom GPTs, deploy large language models, create applications, and in general have a basic understanding of how things work.

Resources - 
Best YouTube Channel to Learn Basic Math Concepts - https://www.youtube.com/@khanacademy
https://www.youtube.com/@3blue1brown

Python playlist - https://www.youtube.com/playlist?list=PLzMcBGfZo4-mFu00qxl0a67RhjjZj3jXm
Python full course - https://youtu.be/rfscVS0vtbw?si=UB94aPRtvGdzqClN

freeCodeCamp Masterclass on DataScience - https://youtu.be/r-uOLxNrNk8?si=1WzkP47ezoV4MU32

Kaggle - https://www.kaggle.com/

Cs50 course on AI - https://cs50.harvard.edu/ai/2024/

Neural Networks full playlist - https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

Building with LLMs - https://www.youtube.com/watch?v=VMj-3S1tku0&list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ

Make sure to take notes and watch till the end.

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CHAPTERS:-
00:00 - WATCH TILL THE END 
00:40 - Basics of AI
00:53 - Important Maths Concepts to Learn
02:06 - Master Python
03:00 - Data Science 
05:11 - Basics of Machine learning
18:06 - Unsupervised learning
19:59 - Reinforcement learning  
22:09 - Neural Networks
27:25 - Basics of Generative AI
30:34 - Conclusion 

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A comprehensive roadmap for learning AI in 2025, starting with foundational mathematics (linear algebra, calculus, probability) and Python programming. The guide covers essential data science libraries (NumPy, Pandas, Matplotlib), then progresses through machine learning concepts including supervised learning (regression, classification algorithms), unsupervised learning (clustering), and reinforcement learning. It explains neural networks, deep learning architectures, and modern generative AI including transformers and large language models. The content includes practical learning resources like Khan Academy, Free Code Camp, and specific YouTube channels for hands-on implementation.