This event has been UPDATED since it was first published. View the UPDATED & Detailed Data engineering with Databricks Training course for beginners Information here.

4 Weekends Data engineering with Databricks Training is being delivered from October 24, 2020 - November 15, 2020 US Pacific time for 16 hours over  4 weekends, 8 sessions, 2 sessions per week, 2 hours per session.

• The medium of instruction is English
• All Published Ticket Prices are in US Dollars.

4 Weekends Data engineering with Databricks Training Schedule

• October 24, 2020 - November 15, 2020 US Pacific time
• 4 Weekends | 2 hours on Saturdays, 2 hours on Sundays every weekend | US Pacific Time
• 8:30 AM - 10:30 AM US Pacific time each of those days
• Please click here to add your location and find your local date and time for the 1st session to be held on October 24, 2020 at 8:30 AM US Pacific Time

Course Overview

• Learn best practices for using Databricks to build data pipelines
• Knowledge and skills that a data engineer would need to build an end-to-end Delta Lake pipeline for streaming and batch data, from raw data ingestion to consumption by end users.

Course Objectives

• Build an end-to-end batch and streaming OLAP data pipeline
• Make data available for consumption by downstream stakeholders using specifiied design patterns
• Apply Databricks' recommended best practices in engineering a single source of truth Delta architecture

Prerequisites

If you do not have any of these prerequisite skills we will be happy to teach you these skills for additional cost before you take Data Engineering with Databricks training course.

• Intermediate to advanced programming skills in Python or Scala
• Intermediate to advanced SQL skills
• Beginning experience using the Spark DataFrames API
• Beginning knowledge of general data engineering concepts
• Beginning knowledge of the core features and use cases of Delta Lake

Who can take Data Engineering with Databricks Course?

• Data Engineers
• Machine Learning Engineers

Course Outline

1. Review of programming with Spark APIs

2. Introduction to key terms and definitions of Databricks data engineering tools

3. Read and Write data with Databricks

4. Work with DataFrames in Databricks

5. Overview of DB Connect, the Spark UI, and writing testable code.

6. Learn about the Cloud Data Platform in terms of data architecture concepts

7. Build an end-to-end OLAP data pipeline using Delta Lake with batch and streaming data

8. Learn best practices