Explore the Foundations of LLMs: Tokenization and Word Embeddings

Enroll in this Free Udemy Course to discover the foundations of LLMs. Start learning today!

Unlock the foundational secrets behind Large Language Models (LLMs) and AI chatbots in this hands-on, beginner-friendly course designed to demystify the core building blocks of modern NLP systems. Whether you’re an aspiring developer, AI enthusiast, or seasoned professional seeking deeper insights, this course offers a clear, intuitive, and practical approach to understanding tokenization and word embeddings—two pillars of LLM architecture. You will gain a true understanding of how and why word embedding models and tokenization work the way they do.

Through over 6 hours of engaging video content, you’ll explore how tokenization transforms raw text into machine-readable units, and how word embeddings capture semantic meaning in multidimensional space. You’ll learn to build your own word embedding models using PyTorch, apply them to real-world tasks like question answering, and even develop a basic mini LLM from scratch. We break down complex mathematical concepts into digestible lessons, ensuring you grasp not just the “how,” but the “why” behind each technique. By the end, you’ll have a solid foundation in the mechanics of LLMs and the confidence to apply these skills in practical AI projects.

No advanced prerequisites—just basic Python and neural network knowledge. If you’re ready to move beyond the hype and truly understand how AI chatbots work under the hood, this course is your launchpad.

What you will learn:

  • Understand how tokenization works and its impact on language processing.
  • Grasp the principles and semantic representation behind word embeddings.
  • Build embedding models with PyTorch and train them on real data.
  • Apply embeddings to practical tasks like question answering.
  • Develop a mini LLM from scratch to see the integration of tokenization and embeddings.
  • Interpret key mathematical concepts in an intuitive and applicable way.

Course Content:

  • Sections: 6
  • Lectures: 30
  • Duration: 6 hours

Requirements:

  • Basic knowledge of python programming
  • Basic knowledge of neural networks

Who is it for?

  • Beginner with basic knowledge of python programming and neural networks seeking true understanding and practical knowledge of LLMs and AI chatbots foundation
  • The AI hobbyist, enthusiast, business manager or anyone who is seeking to just get a clear intuitive overview of the foundation of LLMs and AI chatbots
  • An aspiring developer/professional/practitioner seeking true understanding and practical knowledge of LLMs and AI chatbots foundation
  • An expert/professional in the field seeking to get better true understanding and deeper insights.
  • Anyone seeking practical hands-on knowledge on the very foundations of LLMs and AI chatbots.

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