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Many people use AI tools without understanding what happens beneath the interface.
How AI & LLMs Work is designed to demystify artificial intelligence by explaining how large language models actually function, learn, and generate outputs.
Instead of surface-level tutorials, the course focuses on conceptual clarity.
Foundations Before Applications
The course emphasizes:
- What language models are and are not
- How training data shapes behavior
- Why probabilities drive AI outputs
- The limits of model reasoning
This foundation-first approach anchors How AI & LLMs Work in accurate understanding.
Breaking Down Complex Systems Simply
AI often feels opaque. Ishan Anand – How AI & LLMs Work highlights:
- Core building blocks of modern AI systems
- How tokens, embeddings, and context windows interact
- Why models hallucinate
- How prompt structure influences results
- From Theory to Practical Mental Models
Understanding improves usage. It focuses on:
- Mental models for interacting with LLMs
- Predicting model behavior more reliably
- Avoiding common misconceptions
- Asking better questions of AI systems
These mental models increase the real-world usefulness of the program.
Separating Capability From Hype
AI hype distorts expectations. It reinforces:
- Real strengths of LLMs
- Structural limitations that remain
- When AI excels versus fails
- Responsible interpretation of outputs
This balanced perspective strengthens the credibility of the course.
- Useful Across Technical and Non-Technical Roles
- Product managers working with AI
- Engineers refining system design
- Marketers and strategists using AI tools
- Founders making AI-related decisions
This accessibility broadens the value of the course.
