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Generative AI engineering with Azure Databricks Training

Live Online & Classroom Enterprise Training

Learn to design, build, fine-tune, and deploy generative AI solutions using Azure Databricks and large language models (LLMs).

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What is Generative AI engineering with Azure Databricks Course about?

This course is designed for data professionals and AI engineers who want to harness the power of Generative AI using Azure Databricks. It provides a hands-on, end-to-end learning experience in building, tuning, evaluating, and deploying Large Language Model (LLM) solutions within a scalable and secure enterprise environment.

Participants will begin by understanding the foundations of LLMs and how they’re applied to natural language processing (NLP) tasks. The course then guides learners through advanced architectures like Retrieval-Augmented Generation (RAG) and multi-stage reasoning, empowering them to build intelligent AI workflows that go beyond simple prompting.

What are the objectives of Generative AI engineering with Azure Databricks Course ?

  • Understand the fundamentals of LLMs and their NLP applications
  • Implement RAG pipelines using vector search in Databricks
  • Design multi-stage reasoning systems with frameworks like LangChain, LlamaIndex, or Haystack
  • Fine-tune Azure OpenAI-based language models using Databricks
  • Evaluate LLMs using standard metrics and best practices
  • Apply responsible AI principles and security tooling for LLM deployment
  • Manage LLM life cycles with LLMOps, including deployment and model governance 

Who is Generative AI engineering with Azure Databricks Course for?

  • Data Scientists looking to implement generative AI workflows using LLMs
  • AI/ML Engineers building scalable AI applications in the cloud
  • Azure Data Engineers aiming to extend their skills to LLMOps and AI deployment
  • Technical Architects designing enterprise-grade AI solutions on Azure Databricks
  • Developers with an interest in NLP, RAG, and fine-tuning foundation models

What are the prerequisites for Generative AI engineering with Azure Databricks Course?

  • A basic understanding of machine learning concepts
  • Experience with Python programming
  • Familiarity with Azure services and Databricks platform
  • Some exposure to natural language processing (NLP) is helpful but not mandatory

Available Training Modes

Live Online Training

Course Outline Expand All

Expand All

  • Understand generative AI and LLMs
  • Explore natural language processing (NLP) tasks
  • Run foundational LLM examples in Azure Databricks
  • Understand Databricks integration with Azure OpenAI
  • Understand the lifecycle of a generative AI project
  • Understand what RAG is and why it matters
  • Prepare unstructured data for use with LLMs
  • Create embeddings and implement vector search
  • Implement reranking and response generation
  • Build a complete RAG pipeline using Azure Databricks
  • Understand reasoning and planning for LLMs
  • Learn about multi-stage reasoning frameworks:
  • LangChain
  • LlamaIndex
  • Haystack
  • DSPy
  • Implement prompt chains and memory-based reasoning
  • Use tools and agents to enhance model responses
  • Overview of fine-tuning vs prompting
  • Prepare a dataset for fine-tuning
  • Use Hugging Face, Databricks, and Azure ML for fine-tuning
  • Apply supervised fine-tuning on an LLM
  • Track and version models using MLflow
  • Compare LLM evaluation to traditional ML model evaluation
  • Use metrics: BLEU, ROUGE, perplexity, etc.
  • Implement “LLM-as-a-judge” approach
  • Evaluate tuned models in Databricks workflows
  • Automate evaluation processes
  • Module 6: Implement Responsible AI for LLMs
  • Understand risks of using LLMs (bias, hallucination, etc.)
  • Apply responsible AI principles
  • Use security tools in Databricks to protect data and outputs
  • Enforce ethical AI development in production pipelines
  • Understand differences between MLOps and LLMOps
  • Use MLflow to track, deploy, and manage models
  • Register models with Unity Catalog
  • Deploy LLMs via APIs or apps
  • Automate model lifecycle using workflows and job orchestration

Who is the instructor for this training?

The trainer for this Generative AI engineering with Azure Databricks Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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