Databricks to Local LLMs

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 Lakehouse Platform Fundamentals
• In this module, 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.
• Data Transformation and Pipelines
• In this module, 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.
• Responsible Generative AI
• In this module, 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.
• Local LLMOps
• In this module, you will learn mitigation strategies, evaluate task performance, and operationalize workflows by identifying risks in notebooks and deploying an LLM application.