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. 169
    Summarize Documents with Transformers

    Summarize documents with transformers — Applied AI engineering. Learn core concepts, hands-on steps, troubleshooting, and next steps in this practical tutorial.

  2. 170
    Translate Text with MarianMT

    Learn to translate text with MarianMT in this Applied AI engineering tutorial. Understand the core concept, step-by-step process, hands-on exercise, option comparison, and troubleshooting — ideal for developers seeking practical, Python-native translation skills.

  3. 171
    Implement Whisper Speech-to-Text

    Implement speech-to-text with Whisper — Applied AI engineering tutorial.

  4. 172
    Generate Audio with TTS Models

    Generate audio with TTS models in this Applied AI engineering lesson. Core concepts, hands-on steps, and next steps.

  5. 173
    Build an Image Captioning Model

    Learn to build an image captioning model in Python. This Applied AI engineering lesson covers the core concepts, a step-by-step walkthrough, and practical tips for troubleshooting.

  6. 174
    Object Detection with YOLO

    Implement object detection with YOLO in this hands-on Applied AI engineering tutorial — learn core concepts, step-by-step walkthrough, troubleshooting, and next steps.

  7. 175
    Use GANs for Image Generation

    Use GANs for image generation in this Applied AI engineering tutorial. Learn core concepts, hands-on steps, troubleshooting, and what to study next.

  8. 176
    Build a Time-Series Forecast Model

    Learn to build a time-series forecast model in Python—step-by-step, hands-on, and practical.

  9. 177
    ARIMA Baseline Forecasts

    Use ARIMA for baseline forecasts in this Applied AI engineering tutorial — hands-on steps, troubleshooting, and what to study next.

  10. 178
    Prophet for Business Forecasting

    Prophet for business forecasting — Applied AI engineering.

  11. 179
    LSTM for Multivariate Time Series

    Learn to build an LSTM for multivariate time series — practical steps, troubleshooting, and what to study next in this Applied AI engineering tutorial.

  12. 180
    Detect Anomalies with Autoencoders

    Learn to identify unusual patterns in data using autoencoders. This tutorial covers the core concept, a hands-on Python exercise, troubleshooting tips, and next steps in the Applied AI engineering track.

    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.