Every Databricks badge, and how to earn it

Production streaming patterns in Lakeflow Spark Declarative Pipelines, including expectations, liquid clustering, AUTO CDC for SCD Type 2 and quarantining bad records.

Finish the Advanced Techniques with Spark Declarative Pipeline training (the catalog calls it Advanced Techniques with Apache Spark Declarative Pipelines) in Databricks Academy and pass its quiz with 80% or higher.

Ship Databricks projects through CI/CD with Declarative Automation Bundles, deploying from the CLI, VS Code and GitHub Actions across environments.

Finish the Automated Deployment with Declarative Automation Bundles training in Databricks Academy and pass its quiz with 80% or higher.

Build incremental batch and streaming pipelines in Lakeflow Spark Declarative Pipelines using streaming tables, materialized views and temporary views.

Finish the Build Data Pipelines with Lakeflow Spark Declarative Pipelines training in Databricks Academy and pass its quiz with 80% or higher.

ETL in plain SQL: streaming tables with Auto Loader, materialized views with incremental refresh and AUTO CDC for SCD Type 1 and 2.

Finish the Building ETL Pipelines with SQL training in Databricks Academy and pass its quiz with 80% or higher.

Bring data in with Lakeflow Connect: batch, incremental and streaming loads with CTAS, COPY INTO and Auto Loader, plus rescued data handling.

Finish the Data Ingestion with Lakeflow Connect training in Databricks Academy and pass its quiz with 80% or higher.

Design lakehouse data models that are ready for analytics, covering modeling basics, warehousing and machine learning cases, and data products.

Finish the Data Modeling Strategies training in Databricks Academy and pass its quiz with 80% or higher.

Speed up Spark and Delta Lake workloads: read the Spark UI, then tune streaming, liquid clustering, data skipping, caching and Photon.

Finish the Databricks Performance Optimization training in Databricks Academy and pass its quiz with 80% or higher.

Orchestrate data, analytics and AI work with Lakeflow Jobs: designing task graphs, scheduling, handling errors and building in fault tolerance.

Finish the Deploy Workloads with Lakeflow Jobs training in Databricks Academy and pass its quiz with 80% or higher.

ETL and analytics with the Spark DataFrame API: grouping, aggregations, joins, set operations, window functions and nested data types.

Finish the Developing Applications with Apache Spark™ training in Databricks Academy and pass its quiz with 80% or higher.

Software engineering habits for data engineers on Databricks: code quality, version control, documentation, unit testing and continuous integration.

Finish the DevOps Essentials for Data Engineering training in Databricks Academy and pass its quiz with 80% or higher.

A basic data engineering workflow: ingest into Delta Lake, transform through medallion layers, orchestrate with jobs and query with Databricks SQL.

Finish the Get Started with Databricks for Data Engineering training in Databricks Academy and pass its quiz with 80% or higher.

How Spark spreads work across a cluster, and how to read, write and transform data with the DataFrame API in Python.

Finish the Introduction to Apache Spark™ training in Databricks Academy and pass its quiz with 80% or higher.

Python from zero: expressions, variables, data types, conditions, loops, functions and methods, then a first look at working with data.

Finish the Introduction to Python for Data Science and Data Engineering training in Databricks Academy and pass its quiz with 80% or higher.

Run Spark with Delta Lake on Databricks well: Unity Catalog, ACID tables and maintenance, and query tuning through partitioning and shuffle control.

Finish the Monitoring and Optimizing Apache Spark Workloads on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Process real-time data with Spark Structured Streaming, including streaming aggregations and analysis over time windows.

Finish the Stream Processing and Analysis with Apache Spark™ training in Databricks Academy and pass its quiz with 80% or higher.

MLOps practice for the full model lifecycle: testing, CI/CD, pipeline management, separate environments, scalable design and monitoring.

Finish the Advanced Machine Learning Operations training in Databricks Academy and pass its quiz with 80% or higher.

Explore, clean and shape data for classic machine learning on Databricks, including visualization, feature engineering and storing features.

Finish the Data Preparation for Machine Learning training in Databricks Academy and pass its quiz with 80% or higher.

Design and run feature engineering pipelines on Databricks at scale, from Spark execution and tuning through to MLOps.

Finish the Feature Engineering at Scale training in Databricks Academy and pass its quiz with 80% or higher.

The basic machine learning workflow on Databricks from a practitioner's seat, including feature engineering and simple data science workloads.

Finish the Get Started with Databricks for Machine Learning training in Databricks Academy and pass its quiz with 80% or higher.

When and how to use Spark for preparing data, training and deploying models, with Spark ML and the pandas API on Spark.

Finish the Machine Learning at Scale training in Databricks Academy and pass its quiz with 80% or higher.

Three ways to deploy machine learning models on Databricks: batch inference, pipeline deployment and real-time deployment.

Finish the Machine Learning Model Deployment training in Databricks Academy and pass its quiz with 80% or higher.

Train classic machine learning models on Databricks with common libraries, covering regression, clustering, hyperparameter tuning and experiment tracking.

Finish the Machine Learning Model Development training in Databricks Academy and pass its quiz with 80% or higher.

Core MLOps ideas and model lifecycle management on Databricks, including the model registry in Unity Catalog.

Finish the Machine Learning Operations training in Databricks Academy and pass its quiz with 80% or higher.

Train machine learning models at enterprise scale with SparkML and Ray, plus hyperparameter tuning, MLOps and model governance.

Finish the Model Development at Scale training in Databricks Academy and pass its quiz with 80% or higher.

Measure AI agent quality with MLflow: built-in and custom judges, evaluation datasets, tracing, human feedback and monitoring in production.

Finish the Agent Evaluation on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Production agentic apps with governed tools through Unity Catalog and MCP, single and multi-agent designs, the OpenAI Agents SDK, Agent Bricks and Genie.

Finish the Building Agentic Applications on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Give AI agents short-term and long-term memory with the LangGraph checkpointer and store, using Lakebase to persist it.

Finish the Building Persistent Memory for AI Agents with Lakebase on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Build retrieval agents with Agent Bricks: Knowledge Assistants, document parsing with AI Functions, chunking, Vector Search and several knowledge sources.

Finish the Building RAG Agents with Agent Bricks training in Databricks Academy and pass its quiz with 80% or higher.

Parse and chunk documents, build Vector Search retrieval and develop retrieval agents ready for production on Databricks.

Finish the Building Retrieval Agents On Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Build a single AI agent that uses Unity Catalog functions as tools, with MLflow tracing and frameworks such as LangChain.

Finish the Building Single-Agent Applications on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Deploy agents as Databricks Apps with bundles, add tools through MCP, trace with MLflow and evaluate in production with scorers and judges.

Finish the Deploying and Monitoring Agent Applications on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Put generative AI applications into production with Model Serving, recommended architectures and ongoing monitoring.

Finish the Generative AI Application Deployment and Monitoring training in Databricks Academy and pass its quiz with 80% or higher.

Why generative AI systems need evaluation and governance, and the techniques and security controls for both on Databricks.

Finish the Generative AI Application Evaluation and Governance training in Databricks Academy and pass its quiz with 80% or higher.

What AI agents are made of, and how to build, deploy and evaluate one on Databricks with Mosaic AI and Agent Bricks.

Finish the Get Started with AI Agents on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

An introduction to building and monitoring generative AI apps on Databricks with Vector Search, the Agent Framework and MLflow tracking.

Finish the Get Started with Databricks for Generative AI training in Databricks Academy and pass its quiz with 80% or higher.

Build AI/BI dashboards and Genie spaces as an analyst, and control which business users can see and use them.

Finish the AI/BI for Data Analysts training in Databricks Academy and pass its quiz with 80% or higher.

Ask plain-language questions of governed data in a Genie space, with security and good practice, ending in a hands-on game.

Finish the Answering Business Questions with Databricks Genie training in Databricks Academy and pass its quiz with 80% or higher. The badge page names a different course, which looks like a copy error.

Keep a Databricks warehouse fast, affordable and secure when many users across business units share it.

Finish the Architecting Data Warehouses for Large-Scale Deployments training in Databricks Academy and pass its quiz with 80% or higher.

Set up and tune a Genie space with metadata, synonyms, example SQL, instructions and benchmarks, then share it and watch its answer quality.

Finish the Building Reliable Conversational Agents with Genie training in Databricks Academy and pass its quiz with 80% or higher.

Define business metrics once as Unity Catalog metric views on top of gold tables so analysts work from the same governed KPIs.

Finish the Building Semantic Models in Databricks with UC Metric Views training in Databricks Academy and pass its quiz with 80% or higher.

A beginner's walk through Databricks as a cloud data warehouse, ingesting, transforming, governing and analyzing one dataset, then exploring it with Genie.

Finish the Data Warehousing with Databricks training in Databricks Academy and pass its quiz with 80% or higher.

An overview of the lakehouse approach to data warehousing on Databricks and the AI features that help transform and analyze data.

Finish the Get Started with Databricks for Data Warehousing training in Databricks Academy and pass its quiz with 80% or higher.

First steps as an analyst on Databricks: data objects, SQL queries, Delta Lake features and building dashboards.

Finish the Get Started with SQL Analytics and BI on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Use Databricks SQL to find, query and reshape data and turn it into answers for the business.

Finish the SQL Analytics on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Write modular SQL on Databricks with CTEs, temporary views, UDFs and procedural logic, then schedule it with Lakeflow Jobs.

Finish the SQL Programming and Procedural Logic training in Databricks Academy and pass its quiz with 80% or higher.

Design, build and govern Unity Catalog structures to keep data organized across a large enterprise lakehouse.

Finish the Catalog Management and Data Organization training in Databricks Academy and pass its quiz with 80% or higher.

Unity Catalog governance for large estates: attribute-based access with governed tags, system tables, monitoring, lineage, federated governance and Delta Sharing.

Finish the Data Governance at Scale training in Databricks Academy and pass its quiz with 80% or higher.

Handle personal data on Databricks: Delta Lake design, regional isolation, GDPR and CCPA requests, Change Data Feed and Unity Catalog protections.

Finish the Databricks Data Privacy training in Databricks Academy and pass its quiz with 80% or higher.

Unity Catalog fundamentals: table types, catalogs and schemas, group-based access, row filters and column masks, and moving old access controls over.

Finish the Get Started with Data Governance on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

The basics of running a workspace: Unity Catalog metastores, clusters and SQL warehouses, privileges and fine-grained access control.

Finish the Get Started with Databricks Platform Administration training in Databricks Academy and pass its quiz with 80% or higher. The closing lab exercise comes only with a paid Databricks Labs subscription.

A first tour of the whole platform, from compute and Unity Catalog ingestion to notebooks with Genie Code, dashboards, Genie and MLflow.

Finish the Get Started with Databricks: End to End training in Databricks Academy and pass its quiz with 80% or higher.

An architect's view of the lakehouse on Databricks: what it is for, what it covers and the capabilities that sit on it.

Finish the Get Started with Lakehouse Architecture on Databricks training in Databricks Academy and pass its quiz with 80% or higher.

Build a Databricks App backed by Lakebase from scratch with help from Genie Code, including create, read, update and delete operations.

Finish the Building Databricks Apps with Genie Code and Lakebase training in Databricks Academy and pass its quiz with 80% or higher.

Build and deploy secure data and AI applications with Databricks Apps that people without technical skills can use.

Finish the Building Enterprise Applications with Databricks Apps training in Databricks Academy and pass its quiz with 80% or higher.

An introduction to Databricks Apps for building and deploying secure data and AI applications for business users.

Finish the Get Started with Databricks Apps training in Databricks Academy and pass its quiz with 80% or higher.

Meet Lakebase, the managed Postgres database inside Databricks, with the difference between OLTP and OLAP and the first everyday workflows.

Finish the Get Started with Lakebase training in Databricks Academy and pass its quiz with 80% or higher.

Move data both ways between Lakebase and the lakehouse: federation and governance over Lakebase, reverse ETL into Postgres and CDC back to Delta.

Finish the Lakebase and Lakehouse Integration training in Databricks Academy and pass its quiz with 80% or higher.

Connect a Databricks App to a Lakebase Postgres database and manage the pair; it assumes you already know both products.

Finish the Lakebase App Integration and Management training in Databricks Academy and pass its quiz with 80% or higher.

The starting point of the Lakebase pathway: what Lakebase is, how it is built, your first project and connection, and branching.

Finish the Lakebase First Principles training in Databricks Academy and pass its quiz with 80% or higher.

A Lakebase path for decision makers with no hands-on labs: use cases, a decision framework, architecture, governance and lineage, cost, security and compliance.

Finish the Lakebase for Architects & Decision-Makers training in Databricks Academy and pass its quiz with 80% or higher.

Lakebase for data engineers: ways to query it, day-to-day data work, Unity Catalog governance and synced tables from Delta.

Finish the Lakebase for the Data Engineer training in Databricks Academy and pass its quiz with 80% or higher.

Run Lakebase in production: autoscaling and scale to zero, high availability, read replicas, instant restore, cost, permissions and SOC 2 evidence.

Finish the Lakebase Production Operations training in Databricks Academy and pass its quiz with 80% or higher. The only catalog listing we found for it is a paid lab course.

Migrate a Postgres workload to Lakebase hands on: set up the target, check extension and version parity, cut over, validate and right-size.

Finish the Postgres to Lakebase training in Databricks Academy and pass its quiz with 80% or higher.

Use Unity Catalog as one governance layer so Delta and Iceberg clients can work with the same tables across platforms.

Finish the Data Interoperability with Unity Catalog training in Databricks Academy and pass its quiz with 80% or higher.