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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
1h
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

Runtime

Self-Paced

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

Register now

Instructors

Instructor-Led

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

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Learning

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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Scale

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

Data Ingestion with Lakeflow Connect

This course provides a comprehensive introduction to Lakeflow Connect as a scalable and simplified solution for ingesting data into Databricks from a variety of data sources. You will begin by exploring the different types of connectors within Lakeflow Connect (Standard and Managed), learn about various ingestion techniques, including batch, incremental batch, and streaming, and then review the key benefits of Delta tables and the Medallion architecture.

From there, you will gain practical skills to efficiently ingest data from cloud object storage using Lakeflow Connect Standard Connectors with methods such as CREATE TABLE AS (CTAS), COPY INTO, and Auto Loader, along with the benefits and considerations of each approach. You will then learn how to append metadata columns to your bronze level tables during ingestion into the Databricks data intelligence platform. This is followed by working with the rescued data column, which handles records that don’t match the schema of your bronze table, including strategies for managing this rescued data.

The course also introduces techniques for ingesting and flattening semi-structured JSON data, as well as enterprise-grade data ingestion using Lakeflow Connect Managed Connectors.

Finally, learners will explore alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with foundational knowledge to support modern data engineering ingestion.

Free
2h
Associate

Questions?

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