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LLMOps

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May 1, 2024 Updated July 11, 2025 12 minute read
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Large Language Model Operations (LLMOps) is a rapidly growing field that combines machine learning, data engineering, and software engineering to build, deploy, and manage large language models (LLMs). LLMs are powerful AI models that can understand and generate human-like text, making them ideal for a wide range of applications, from customer service chatbots to language translation and content creation.

Why Learn LLMOps?

There are several reasons why you might want to learn LLMOps:

Path to LLMOps

Take the first step.
We've curated seven courses to help you on your path to LLMOps. Use these to develop your skills, build background knowledge, and put what you learn to practice.
Sorted from most relevant to least relevant:

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Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in LLMOps.
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Mapping Applied Linguistics
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Provides a comprehensive overview of LLMs, covering their history, architecture, and applications. It great resource for anyone who wants to learn more about LLMs and their potential.
Mapping Applied Linguistics
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Mapping Applied Linguistics
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Neural Network Methods in Natural Language...
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Provides a comprehensive overview of the theory and practice of language modeling. It covers a wide range of topics, from the basics of language modeling to the latest advances in deep learning-based models.
Neural Network Methods in Natural Language...
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Neural Network Methods in Natural Language...
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Statistical Machine Translation
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Focuses on the use of LLMs for machine translation. It provides detailed instructions on how to train and evaluate LLMs for machine translation, and how to use them to translate text between different languages.
Statistical Machine Translation
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Statistical Machine Translation
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Automatic Summarization
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Focuses on the use of LLMs for summarization. It provides detailed instructions on how to train and evaluate LLMs for summarization, and how to use them to generate high-quality summaries of text.
Automatic Summarization
Paperback
$$$
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Linguistic Fundamentals for Natural Language...
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Focuses on the use of LLMs for dialogue generation. It provides detailed instructions on how to train and evaluate LLMs for dialogue generation, and how to use them to generate high-quality dialogue.
Linguistic Fundamentals for Natural Language...
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Linguistic Fundamentals for Natural Language...
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Model Risk in Financial Markets
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Focuses on the use of LLMs for financial modeling. It provides detailed instructions on how to train and evaluate LLMs for financial modeling, and how to use them to develop financial models.
Model Risk In Financial Markets: From Financial...
Paperback
$$$$
Model Risk In Financial Markets: From Financial...
Kindle Edition
$$$
Relevant careers
Data Scientist
Machine Learning Engineer
Software Engineer
Cloud Architect
Natural Language Processing Engineer
AI Researcher
Data Analyst
DevOps Engineer
Related topics
Large Language Models (LLMs)
Deep Learning
Data Engineering
Machine Learning
Natural Language Processing (NLP)
Artificial Intelligence (AI)
Software Engineering
Cloud Computing
DevOps
Data Science
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