By the end of this course, a learner will master Databricks to perform data engineering and data analytics tasks for data science workflows. Additionally, a student will learn to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Databricks to Local LLMs
This course is part of Large Language Model Operations (LLMOps) Specialization
Taught in English
Some content may not be translated
Instructors: Noah Gift
Included with
Course
Recommended experience
What you'll learn
Databricks
ML pipelines
llamafile and other local LLMs like Mixtral
Skills you'll gain
Details to know
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February 2024
15 quizzes
Course
Recommended experience
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There are 4 modules in this course
This week, you will learn how to describe the Databricks architecture, create clusters, use notebooks for analysis, and share notebooks by completing hands-on labs and knowledge checks on these topics.
What's included
25 videos13 readings4 quizzes1 discussion prompt2 ungraded labs
This week, you will learn how to read and transform data, create Delta Lake pipelines, and work with complex data types by implementing ETL solutions and passing code samples reviews.
What's included
23 videos9 readings4 quizzes3 ungraded labs
This week you will learn foundations of generative AI and responsible deployment strategies to benefit from the latest advancements while maintaining safety, accuracy, and oversight. By directly applying concepts through hands-on labs and peer discussions, you will gain practical experience putting AI into production.
What's included
13 videos14 readings4 quizzes3 ungraded labs
This week, you will learn mitigation strategies, evaluate task performance, and operationalize workflows by identifying risks in notebooks and deploying an LLM application.
What's included
13 videos10 readings3 quizzes
Offered by
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