Go beyond API calls and prompt engineering. Master the mathematics, build models from scratch, deploy production-ready systems, and develop critical thinking to know when GenAI is the right solution—and when it isn't. A comprehensive journey from neural network fundamentals to expert-level GenAI engineering.
From foundational mathematics to production deployments. Each module builds systematically on previous concepts, ensuring you understand not just how to use GenAI tools, but how they work internally and how to architect your own solutions from scratch.
GenAIHub.live is your comprehensive resource for mastering Generative AI from first principles to production deployment. Unlike courses focused solely on API usage, we teach you to build, deploy, and critically evaluate GenAI systems from the ground up. Our structured curriculum progresses systematically from mathematical foundations through production deployment, ensuring you develop the deep technical understanding required for expert-level AI engineering.
Focus on the essentials—linear algebra, probability, and optimization concepts that directly power modern AI. Understand the mathematical foundations that explain why transformers work, not just that they do.
Implement neural networks, transformers, and RAG systems from first principles. Write actual code instead of just calling APIs. Develop deep understanding through rigorous hands-on implementation.
Develop judgment to identify when GenAI is the right solution—and when it isn't. Understand costs, limitations, and architectural tradeoffs. Make informed technical decisions backed by deep understanding.
Deploy production-ready systems at scale. Master MLOps, security, evaluation metrics, and infrastructure management. Build reliable, maintainable systems—not just proof-of-concept demos.
Read academic papers effectively, critically evaluate claims, and stay current with rapidly evolving research. Separate genuine breakthroughs from hype and position yourself to contribute meaningfully to the field.
Build secure, responsible AI systems. Understand prompt injection vulnerabilities, data privacy requirements, bias mitigation, and regulatory compliance. Deploy AI systems that are both powerful and trustworthy.
Start with the foundations—math, Python, and neural networks. Progress through transformers, LLMs, RAG, agents, and production deployment. Transform from beginner to expert with a structured, comprehensive curriculum designed for real-world impact.
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