Introduction to Core LLM concepts

A Complete Code-Free Guide

Feel left behind by the AI revolution because you don't know Python? This course is your gateway to the exciting world of Large Language Models, specifically designed for Java developers who want to understand and implement AI without changing their tech stack.

Through clear, jargon-free explanations, you'll discover how LLMs actually work - from their fundamental architecture and tokenization to sophisticated prompting techniques and integration patterns. We explore everything from the basics of what AI truly is to advanced concepts like context windows, structured outputs, and error handling strategies.

The curriculum methodically builds your knowledge: starting with AI and LLM foundations, moving to practical Java integration with HTTP, then advancing to conversation management, prompting patterns, and robust error handling. Each concept is explained in plain English with practical insights.

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    From Java to AI: The Python-Free Guide to Large Language Models

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What is covered

Zero-to-hero understanding of LLMs that lets you join AI discussions with confidence

  • The fundamentals of AI and LLMs explained in simple, accessible language without mathematical complexity

  • How modern language models actually work under the hood

  • Text processing and tokenization explained with practical implications for your applications

  • Crafting effective prompts that produce consistent, reliable results for business applications

  • Managing contextual conversations with stateless LLMs through proper session handling

  • Tuning LLM parameters to control creativity, response length, and output variety

  • Error handling strategies for dealing with the unique challenges of AI-generated content

  • Context window optimization to handle lengthy interactions efficiently

  • Validation strategies for verifying LLM responses to prevent incorrect or hallucinated information

Course curriculum

    1. About this course

      FREE PREVIEW

    2. What is AI really?

      FREE PREVIEW

    3. How is AI Different From Traditional Software?

    4. The BEST Explanation of AI Training

    5. Challenges and Pitfalls in AI Training

    6. AI vs. Machine Learning - What's The Difference?

    1. What are Language Models?

    2. What does a model look like?

    3. Why "large" language models?

    4. Understanding typical sizes of LLMs

    5. Training an LLM - what actually gets adjusted?

    6. What about conflicts in training?

    7. LLM size - Is more always better?

    1. How LLMs process text

    2. How big are tokens?

    3. Tokenizer types

    4. Tokenizer Visualizer

    1. Four Capabilities of LLMs

    2. Running Language model locally using Ollama

    3. Integration for Java Developers

    1. Prompting and how it works

    2. The rationale behind prompting

    3. Chain of thought prompting

    4. Single-turn and Multi-turn interactions

    5. LLMs are stateless

    1. Tokens and Context Windows

    2. Context window precision and tradeoffs

    3. Structured Messages - System, Assistant and User

    4. Some examples of structured messages

    5. Context window truncation - Bye bye system message?

    6. Questions about system message answered

About this course

  • $50.00
  • 41 lessons
  • 5.5 hours of video content

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