Databricks Data Intelligence Platform: full course guide
The whole Databricks platform in one guide: the lakehouse and Delta Lake, data engineering with Spark and declarative pipelines, SQL warehousing, Unity Catalog governance, machine learning with MLflow, and generative AI with Vector Search, agents and AI/BI Genie, with runnable examples throughout.
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What is inside this guide
01Databricks Platform Foundations
- Lakehouse Architecture & Workspace Setup
- Compute: Clusters, Pools & Serverless
- Unity Catalog Fundamentals
- Notebooks, Repos & Git Integration
- Jobs & Workflow Orchestration
02Delta Lake & Lakehouse Storage
- Delta Format & the Transaction Log
- ACID Transactions & Time Travel
- OPTIMIZE, Z-Order & Liquid Clustering
- Schema Evolution & Table Constraints
- Delta Sharing & Marketplace
03Data Engineering with Spark
- Spark on Databricks & Photon Engine
- Auto Loader & Incremental Ingestion
- Lakeflow Declarative Pipelines (DLT)
- Medallion Architecture in Practice
- Structured Streaming & Change Data Capture
04Databricks SQL & Analytics
- SQL Warehouses & Query Execution
- Query Tuning, Caching & Cost Control
- Materialized Views & Streaming Tables
- Dashboards, Alerts & Data Apps
- Lakehouse Federation & External Data
05Governance, Security & Operations
- Unity Catalog Privileges & Lineage
- Identity, SCIM & Credential Management
- Secrets, Networking & Data Isolation
- System Tables, Auditing & Observability
- CI/CD with Asset Bundles & Terraform
06Machine Learning Engineering
- Feature Engineering in Unity Catalog
- Experiment Tracking with MLflow
- AutoML & Distributed Training
- Model Registry & Model Serving
- Lakehouse Monitoring & Drift Detection
07Generative AI & AI/BI Genie
- Vector Search & Embedding Pipelines
- Retrieval Augmented Generation on Databricks
- Foundation Model APIs & Fine Tuning
- Mosaic AI Agent Framework & Tool Calling
- AI/BI Genie Spaces & Natural-Language Analytics
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