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Microsoft Copilot & Azure AIDP-3028 Implement Generative AI engineering with Azure Databricks
Engineer generative AI on Azure Databricks.
1 dayIntermediate7 modulesDP-3028
About this course
Engineer generative AI on Azure Databricks. In one day you will work with language models, implement retrieval-augmented generation and multi-stage reasoning, fine-tune and evaluate models, and apply responsible AI.
Curriculum
7 modules
- Understand Generative AI
- Understand Large Language Models (LLMs)
- Identify key components of LLM applications
- Use LLMs for Natural Language Processing (NLP) tasks
- Explore the main concepts of a RAG workflow
- Prepare your data for RAG
- Find relevant data with vector search
- Rerank your retrieved results
- What are multi-stage reasoning systems?
- Explore LangChain
- Explore LlamaIndex
- Explore Haystack
- Explore the DSPy framework
- What is fine-tuning?
- Prepare your data for fine-tuning
- Fine-tune an Azure OpenAI model
- Explore LLM evaluation
- Evaluate LLMs and AI systems
- Evaluate LLMs with standard metrics
- Describe LLM-as-a-judge for evaluation
- What is responsible AI?
- Identify risks
- Mitigate issues
- Use key security tooling to protect your AI systems
- Transition from traditional MLOps to LLMOps
- Understand model deployments
- Describe MLflow deployment capabilities
- Use Unity Catalog to manage models
Who it's for
Data engineers and ML engineers using Databricks.
Before you start
- Before starting this module, you should be familiar with fundamental Azure Databricks concepts
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