Databricks
Advanced Learning Festival
📅 September 16 – October 14, 2026
🎉 Join us for a four-week event dedicated to learning, upskilling, and advancing your career in data engineering, analytics, machine learning, and generative AI. Whether you are new to the field or aiming to deepen your knowledge, this is a great opportunity to invest in your professional development alongside a global community.
🎟️ Finish all modules in at least one learning pathway during the event window to receive:
50% OFF any Databricks Certification
20% OFF a yearly Databricks Academy Labs subscription
💬 Incentives distributed: to the email associated with your Customer Academy account on October 19, 2026, after the event concludes.
⚠️ Important: ensure every component of a course is marked complete (including any introduction sections) within the eligibility window so your pathway is properly recorded.
🔑 Registering to redeem your voucher
When you register for your WebAssessor account, please use the same email address associated with your Databricks Customer Academy account. Vouchers for this event are scoped to that email and can only be redeemed by it. If you already have a WebAssessor account under a different email, you can add your Academy email as a secondary email on your existing account.
Choose Your Learning Pathway
Start exploring your options below and enroll through Customer Academy.
🛠️ Associate Data Engineering
Complete all 4 modules from the Data Engineer Learning Plan:
Data Ingestion with Lakeflow Connect
Deploy Workloads with Lakeflow Jobs
Build Data Pipelines with Lakeflow Spark Declarative Pipelines
DevOps Essentials for Data Engineering
⚙️ Professional Data Engineering
Complete all 4 modules from the Data Engineer Learning Plan:
Advanced Techniques with Spark Declarative Pipelines
Databricks Data Privacy
Databricks Performance Optimization
Automated Deployment with Declarative Automation Bundles
📊 Data Analysts
Complete both modules from the Data Analyst Learning Plan:
AI/BI for Data Analysts
SQL Analytics on Databricks
🤖 Associate ML Practitioners
Complete all 4 modules from the Machine Learning Practitioner Learning Plan:
Data Preparation for Machine Learning
Machine Learning Model Development
Machine Learning Model Deployment
Machine Learning Operations
🧠 Professional ML Practitioners
Complete both modules from the Machine Learning Practitioner Learning Plan:
Machine Learning at Scale
Advanced Machine Learning Operations
✨ Generative AI Engineering
Complete all 4 modules from the Generative AI Engineering Learning Plan:
Building RAG Agents with Databricks
Building Agentic Applications on Databricks
Agent Evaluation on Databricks
Deploying and Monitoring Agent Applications on Databricks
🔥 Apache Spark™ Developer
Complete all 4 modules from the Apache Spark™ Developer Learning Plan:
Introduction to Apache Spark™
Developing Applications with Apache Spark™
Stream Processing and Analysis with Apache Spark™
Monitoring and Optimizing Apache Spark™ Workloads on Databricks
🏛️ Data Warehousing Practitioner
Complete all 4 modules from the Data Warehousing Practitioner Learning Plan:
SQL Programming and Procedural Logic in Databricks
Data Modelling Strategies
Building Semantic Models in Databricks with UC Metric Views
Architecting Data Warehouses for Large-Scale Deployments
Read the full FAQ →
Happy learning! 📚🎓🧑💻
Virtual Event
Time: AMER Nov 10 / 10 AM PT APJ Nov 11 / 9:30 AM IST / 12 PM SGT / 1 PM JST/KST / 3 PM AEDT (Japanese and Korean captions available) EMEA Nov 12 / 9 AM GMT / 10 AM CET
🔗 Register for the Workshop
Note: Marking RSVP on this Community event does not register you for the workshop. Please use the Register button above to complete your registration on the official event page.
The Emerging Blueprint for Agentic Apps: Why Postgres is the foundation for a new data processing architecture Providing your agent with live application state, historical data, and a unified security model usually means stitching together infrastructure with pipelines you need to monitor and fix.
Join Reynold Xin (Co-founder and Chief Architect, Databricks) and Jonathan Katz (Sr. Staff Product Manager, Databricks) for an overview of Lake Transactional/Analytical Processing (LTAP), a new architecture that lets transactions and analytics read from the same copy of data in open formats on standard Postgres, along with a live demo.
Key Takeaways:
Unified Security: See how LTAP brings agent memory, application state, and historical data under the same permissions.
Eliminate Pipeline Bottlenecks: Learn to remove sync intervals as a bottleneck for the agent memory loop while maintaining performance and availability.
Seamless Compatibility: Maintain compatibility with your existing drivers, extensions, and ORMs by running on standard Postgres.
Post-Event Resources: Registrants will receive resources to further explore the presented materials after the event.
Agenda (60 Minutes):
Why Agentic Scale Is Breaking Legacy Infrastructures (15 mins)
A Deep Dive Into LTAP Architecture (15 mins)
Demo: Unifying Real-Time Operational and Analytical Data (15 mins)
Enterprise Patterns: Where LTAP Delivers Value Today (15 mins)
