Mastering LLMOps: New Free Course by

Image source: Analytics Drift launches a 1-hour course on LLMOps, a dive into customizing Large Language Models (LLMs) for specific applications.

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Course Introduction

Discover the LLMOps pipeline: From pre-processing data for instruction tuning to deploying tailored LLMs like a Python Q&A chatbot.

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The LLMOps Pipeline

Learn to retrieve, transform, and version data for LLM fine-tuning, tracking experiments with precision.

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Key Learning Steps

Configure and execute an open-source supervised tuning pipeline, gaining hands-on experience in model training and deployment.

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Supervised Tuning Pipeline

Focus on responsible AI by monitoring safety scores and filtering behavior in LLM applications.

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Ensuring Safe Deployment

Engage with the deployed LLM within the course, experiencing the direct results of your tuning efforts.

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Interactive Learning Experience

Get practical with tools like BigQuery, Kubeflow Pipelines, and Google Cloud, essential for LLMOps.

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Tools for LLMOps Mastery

AI enthusiasts and professionals seeking to tune LLMs and build robust LLMOps pipelines are invited to join.

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Who Should Enroll

Adapt open-source pipelines, version data and models, and process datasets in a data warehouse—all covered in the course.

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Course Highlights

Led by Erwin Huizenga, Machine Learning Technical Lead at Google, the course offers expert insights into LLMOps.

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Produced by: Analytics Drift Designed by: Prathamesh