Databricks AI Security Fundamentals

In this course, you will explore the fundamentals of security in AI systems within the Databricks Data Intelligence Platform. The course covers five comprehensive modules and delves into the significance of securing AI systems and navigating compliance with evolving legal and regulatory standards. You will examine recent security incidents, identify various AI model types, and assess security risks across AI system components. Additionally, you will learn to leverage Databricks features for enhanced AI security, illustrating best practices for risk mitigation. By the end of the course, you will possess the knowledge and skills necessary to implement secure AI solutions and apply effective security measures in real-world scenarios.

Skill Level

Introductory

Duration

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

Basic knowledge of cloud computing and data governance techniques.

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

See all our registration options

Registration options

Databricks has a delivery method for wherever you are on your learning journey

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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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

Databricks Data Privacy

This content provides a comprehensive guide to managing data privacy within Databricks. It covers key topics like Delta Lake architecture, regional data isolation, GDPR/CCPA compliance, and Change Data Feed (CDF) usage. Through practical demos and hands-on labs, participants learn to use Unity Catalog features to secure sensitive data and ensure compliance, empowering them to safeguard data integrity effectively.

Note: This course is the second in the 'Advanced Data Engineering with Databricks' series.

Free

Professional

Data Architect

Data Modeling Strategies

This course offers a deep dive into designing data models within the Databricks Lakehouse environment, and understanding the data products lifecycle. Participants will learn to align business requirements with data organization and model design leveraging Delta Lake and Unity Catalog for defining data architectures, and techniques for data integration and sharing.

Free

Associate

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.

Note: This course is the fourth in the 'Advanced Data Engineering with Databricks' series.

Free

Professional