Andrew Ng’s DeepLearning.AI has come up with a free short course, LLMOps, offered in collaboration with Google Cloud. The course is designed in a way that beginners find it easy to learn in one hour of instruction by Erwin Huizenga, a Machine Learning Technical Lead at Google. The target audience includes individuals interested in tuning LLMs and building LLMOps pipelines.

Participants will gain practical knowledge on adapting an open-source pipeline to implement supervised fine-tuning on an LLM for better user question responses. The course emphasises best practices, such as data and model versioning, and covers the pre-processing of substantial datasets within a data warehouse.

Responsible AI practices are also addressed, focusing on the output of safety scores for sub-categories of potentially harmful content. They will also delve into the LLMOps pipeline, learning to retrieve and transform training data, version data and tuned models, configure an open-source supervised tuning pipeline, and deploy a tuned LLM. 

The course comes with practical applications which include creating a customised question-answer chatbot, like one for Python coding queries. BigQuery data warehouse, open-source Kubeflow Pipelines, and Google Cloud are some of the tools taught in this course. 

Ng had earlier partnered with Google Cloud for the course ‘Understanding and Applying Text Embeddings with Vertex AI’ which focussed on leveraging text embeddings to capture the essence of sentences and paragraphs. 

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