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. 145
    Applied AI engineering — Part 075

    Placeholder slot — edit in console (python-artificial-intelligence-stub-075).

  2. 146
    Optimize Inference with ONNX

    Optimize inference with ONNX — Applied AI engineering.

  3. 147
    Applied AI engineering — Part 076

    Placeholder slot — edit in console (python-artificial-intelligence-stub-076).

  4. 148
    Quantize Models for Edge

    Learn to quantize models for edge devices in this Applied AI engineering tutorial — hands-on steps, troubleshooting, and what to study next.

  5. 149
    Applied AI engineering — Part 077

    Placeholder slot — edit in console (python-artificial-intelligence-stub-077).

  6. 150
    TensorFlow Serving: Model Deployment

    Serve models with TensorFlow Serving — Applied AI engineering.

  7. 151
    Speed Up Predictions with ONNX Runtime

    Learn to speed up model predictions using ONNX Runtime. This tutorial covers conversion, optimization, and hands-on exercises.

  8. 152
    Batch Prediction Pipelines

    Learn to build batch prediction pipelines in Python: process large datasets efficiently, handle errors, and scale for production.

  9. 153
    Stream Predictions with Kafka

    Stream predictions with Kafka — Applied AI engineering.

  10. 154
    Implement Online Learning with SGD

    Learn to implement online learning with SGD in Python. This step-by-step tutorial explains how to update models incrementally, shows a hands-on exercise, and covers troubleshooting tips for streaming data.

  11. 155
    Use Ray for Distributed Training

    Learn how to use Ray for distributed training in this Applied AI engineering tutorial. Hands-on steps, practical examples, and what to study next.

  12. 156
    Scale Training with Horovod

    Scale training with Horovod — Applied AI engineering.

    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.