LLM Engineering & Generative AI · Tutorial tracks

Applied AI engineering

LLM APIs, structured outputs, retrieval, evaluation harnesses — Python-native application focus.

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Lesson outline

  1. 73
    Applied AI engineering — Part 039

    Placeholder slot — edit in console (python-artificial-intelligence-stub-039).

  2. 74
    Compile Models with Optimizers

    Compile models with optimizers and loss in Applied AI engineering — practical steps, comparisons, and troubleshooting for Python developers.

  3. 75
    Applied AI engineering — Part 040

    Placeholder slot — edit in console (python-artificial-intelligence-stub-040).

  4. 76
    Fit Models with Batched Training

    Learn to fit models with batched training in this Applied AI engineering step. Core concepts, hands-on practice, and next steps included.

  5. 77
    Applied AI engineering — Part 041

    Placeholder slot — edit in console (python-artificial-intelligence-stub-041).

  6. 78
    Evaluate Neural Networks

    Learn to evaluate neural networks on test data in this Applied AI engineering tutorial. Step-by-step, practical, with troubleshooting and next steps.

  7. 79
    Applied AI engineering — Part 042

    Placeholder slot — edit in console (python-artificial-intelligence-stub-042).

  8. 80
    Prevent Overfitting with Dropout

    Learn how dropout layers prevent overfitting in neural networks. This step-by-step Applied AI engineering tutorial covers core concepts, hands-on implementation, practical comparisons, and common edge cases.

  9. 81
    Applied AI engineering — Part 043

    Placeholder slot — edit in console (python-artificial-intelligence-stub-043).

  10. 82
    Add Batch Normalization for Stability

    Learn to add batch normalization for stability in your neural networks. This hands-on tutorial explains the concept, shows step-by-step implementation, and covers troubleshooting and best practices for stable training.

  11. 83
    Applied AI engineering — Part 044

    Placeholder slot — edit in console (python-artificial-intelligence-stub-044).

  12. 84
    Keras Custom Callbacks

    Learn to create custom callbacks in Keras for better training control. This Applied AI engineering tutorial covers how to implement callbacks to monitor metrics, adjust learning rates, and more, with a hands-on exercise to solidify your skills.

    Applied AI engineering — step-by-step tutorials

    What you will find here

    This track walks through applied ai engineering in order — each lesson is server-rendered HTML you can read without JavaScript. Follow the outline, then practice in the browser IDE when a lesson links to runnable code.

    Tutorials vs quizzes and code samples

    Tutorials teach in sequence. For quick checks use quizzes. For copy-paste snippets see code samples. For deeper reading browse articles.