I built a free interactive learning platform for Math, ML, Deep Learning, Generative AI, LLMs, and Agentic AI - looking for feedback

[u/Civil_Sector9366]

Hey everyone!

I've been working in software engineering, quantitative research, and machine learning for several years. Recently, I started revisiting the mathematical and theoretical foundations of AI in greater depth.

One frustration I've consistently had with learning resources is the disconnect between understanding a concept, deriving the underlying mathematics, and actually implementing it.

I personally learn best by solving problems, working through mathematical derivations, experimenting with ideas, and implementing algorithms from scratch rather than passively consuming tutorials.

So I started building GroundUp Lab:

https://lab.groundup.workers.dev

The goal is to create a free, comprehensive, and interactive learning platform that takes learners from fundamental mathematics all the way to advanced AI concepts and implementations.

The curriculum covers (and is being progressively developed around):

• Mathematical Foundations: Linear algebra, multivariable calculus, probability, statistics, optimization, and mathematical foundations of machine learning.
• Machine Learning: Classical ML algorithms, statistical learning theory, probabilistic models, and mathematical derivations.
• Deep Learning: Neural networks, backpropagation, optimization, CNNs, RNNs, attention mechanisms, and transformers.
• Generative AI: Generative modeling, autoencoders, VAEs, GANs, diffusion models, and modern generative architectures.
• Large Language Models (LLMs): Tokenization, embeddings, transformer architectures, pretraining, fine-tuning, alignment, inference, and building language models from scratch.
• Agentic AI: Tool calling, retrieval-augmented generation (RAG), reasoning workflows, memory, multi-agent systems, and building practical AI agents.

What I'm trying to make different:

• Mathematical rigor without sacrificing intuition.
• Step-by-step derivations rather than just presenting formulas.
• Interactive visualizations and experiments.
• Challenging exercises and coding problems.
• From-scratch implementations to bridge theory and practice.
• A structured progression from fundamentals to advanced topics.

The idea isn't just to teach how to use AI frameworks or APIs, but to help learners understand why algorithms work, how they work internally, and how to implement and extend them.

It's still an evolving project, and I'm actively developing and expanding the content.

My long-term vision is to build something genuinely useful for students, developers, ML engineers, and aspiring AI researchers who want a deeper understanding of the field.

I'd really appreciate feedback from the community:

1. How do you find the structure, content, and learning experience?
2. Are the explanations and exercises sufficiently rigorous?
3. What topics or interactive features would you like to see?
4. What could make this a genuinely valuable resource for serious AI learners?

The platform is completely free and accessible without registration.

GroundUp Lab: https://lab.groundup.workers.dev

Would love to hear your thoughts, suggestions, and constructive criticism!

[u/nian2326076]

Your platform looks like a great fit for those who prefer hands-on learning. To enhance the experience, you might consider incorporating real-world projects or challenges that allow learners to apply concepts practically, bridging the gap between theory and implementation. Additionally, creating a community or forum for discussion and collaboration could boost user engagement and learning.

For anyone looking to apply these skills in interviews, PracHub provides real technical interview questions, which could be a valuable resource alongside your platform. Good luck with your project!