Build and expand your data skills by attending this class and asking questions to our Databricks experts, taking place between 21 and 23 February.

Onboarding Standard course consists of 3-day sessions: 1) Cluster Creation and Sizing; 2) Introduction to Data Engineering with Delta Lake; and 3) Introduction to Data Science on Databricks with MLflow. Upon completion of course (attend at least 1 of 3 sessions), survey, and accreditation, you will receive a 75% certification voucher to take on a Databricks certification exam for the course.

Activate Training Series - Onboarding Standard

Tuesday 21 February - Thursday 23 February
9:30 AM-10:30 AM IST

12:00 PM-1:00 PM SGT

3:00 PM-4:00 PM AEDT

Day 1: Cluster Creation and Sizing

In this 1-hour session, you will learn the basics about clusters, cost management, access control levels and governance from an experienced Customer Success Engineer (CSE), to help you get started with your projects. This session is relevant to platform admins and anyone managing clusters and/or access controls.

Topics covered:

• Pricing and cost review – quick highlights of DBU and pricing structure
• Governance – who can create clusters?
• Architecting clusters – how to create the most efficient clusters
• Cluster sizing – how large to make your clusters
• Q&A

Day 2: Introduction to Data Engineering with Delta Lake

During this 1-hour session, you will learn about the Delta Lake Open Source project, the Lakehouse architecture, and the different Delta Lake features. Participants will also gain insight into big data limitations and bottlenecks and best practices around scaling out data lakes efficiently.

Topics covered:

• Lakehouse & Delta Lake introduction
• Delta Lake features deep dive
• Delta Lake architecture patterns – Bronze / Silver / Gold pipeline
• Reconciling batch and streaming
• Demo
• Q&A

Day 3: Introduction to Data Science on Databricks with MLflow

During this 1-hour session, you will learn about the different MLflow components and how to use MLflow to track, register and serve your machine learning models.

Topics covered:

• Introduction to MLflow
• MLflow demo
• Train a single node ML model and log the results in MLflow
• MLflow UI walkthrough
• MLflow API
• Q&A

Registration is now closed