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Generative AI Application Deployment and Monitoring

Ready to learn how to deploy, operationalize, and monitor generative AI applications? This content will help you gain skills in the deployment of generative AI applications using tools like Model Serving. We’ll also cover how to operationalize generative AI applications following best practices and recommended architectures. Finally, we’ll discuss the idea of monitoring generative AI applications and their components using Lakehouse Monitoring.


Languages Available: English | 日本語 | Português BR | 한국어

Skill Level
Associate
Duration
4h
Prerequisites
  • Familiarity with natural language processing concepts
  • Familiarity with prompt engineering/prompt engineering best practices 
  • Familiarity with the Databricks Data Intelligence Platform
  • Familiarity with RAG  (preparing data, building a RAG architecture, concepts like embedding, vectors, vector databases, etc.)
  • Experience with building LLM applications using multi-stage reasoning LLM chains and agents
  • Familarity with Databricks Data Intelligence Platform tools for evaluation and governance. 



Outline

Model Deployment Fundamentals

  • Model Management
  • Deployment Methods


Batch Deployment

  • Introduction to Batch Deployment
  • Batch Inference
  • Batch Inference Workflows using SLM


Real-Time Deployment

  • Introduction to Real-Time Deployment
  • Databricks Model Serving
  • Serving External Models with Model Serving
  • Deploying an LLM Chain to Databricks Model Serving 
  • Custom Model Deployment and A/B Testing


AI System Monitoring

  • AI Application Monitoring
  • Online Monitoring an LLM RAG Chain


LLMOps Concepts

  • MLOps Primer
  • LLMOps vs MLOps

Upcoming Public Classes

Date
Time
Language
Price
Apr 28
01 PM - 05 PM (America/New_York)
English
$750.00
May 01
09 AM - 01 PM (Asia/Kolkata)
English
$750.00
May 27
09 AM - 01 PM (America/New_York)
English
$750.00
May 28
09 AM - 01 PM (Europe/London)
English
$750.00
May 29
01 PM - 05 PM (Asia/Kolkata)
English
$750.00
Jun 30
01 PM - 05 PM (Europe/London)
English
$750.00
Jul 01
01 PM - 05 PM (America/New_York)
English
$750.00
Jul 02
09 AM - 01 PM (Asia/Kolkata)
English
$750.00
Jul 29
09 AM - 01 PM (Europe/London)
English
$750.00
Jul 30
09 AM - 01 PM (America/New_York)
English
$750.00
Jul 30
09 AM - 01 PM (America/New_York)
English
$750.00
Aug 01
01 PM - 05 PM (Asia/Kolkata)
English
$750.00

Public Class Registration

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Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Data Engineer

Automated Deployment with Databricks Asset Bundles

This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.

The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Databricks Asset Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Databricks Asset Bundles for multiple environments with different configurations using the Databricks CLI.

Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Databricks Asset Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Databricks Asset Bundles.

By the end of this course, you will be equipped to automate Databricks project deployments with Databricks Asset Bundles, improving efficiency through DevOps practices.

Languages Available: English | 日本語 | Português BR | 한국어

Paid
4h
Lab
instructor-led
Professional

Questions?

If you have any questions, please refer to our Frequently Asked Questions page.