ExistBI offers Databricks training for Developers, Data Engineers, Data Science Engineers, Programmers and Data Analysts. Click the Databricks training your interested below to get a more in-depth outline of class modules, pre-requisites, logistics, available dates and how to book:
- Data Engineering with Databricks For Beginners (2-day)
- Advanced Data Engineering (2-day)
- Intro to Databricks: Certified Associate Developer Exam (3-day)
- Apache Spark™ Programming with Databricks (2-day)
- Data Analysis with Databricks SQL (1-day)
- Introduction to Python (2-day)
- Optimizing Apache Spark™ on Databricks (2-day/Custom)
- Scalable Machine Learning with Apache Spark™ (2-day)
All of our Databricks trainers are certified and enthusiastic!
The Databricks courses are offered privately onsite or via public live instructor-led online virtual classroom. All private Databricks classes can be customized for your specific requirements.
All delegates receive the relevant course materials (student guide and labs) and access to a licensed environment for hands-on labs (if required).
For online training, we use a daily Teams, WebEx or Zoom meeting to view the trainer screen and for audio communication.
Databricks Training Outlines
Data Engineering with Databricks For Beginners: This course introduces best practices for using Databricks to build data pipelines through lectures and hands-on labs. Topics include data ingestion and processing techniques, building and executing data pipelines with Delta Live Tables and Databricks Workflows, and data governance with Unity Catalog. At the end of the course, you will have all the knowledge and skills that a data engineer would need to build an end-to-end Delta Lake pipeline for streaming and batch data.
Advanced Data Engineering: In this course, students will build upon their existing knowledge of Apache Spark™, Structured Streaming and Delta Lake to unlock the full potential of the data lakehouse by utilizing the suite of tools provided by Databricks. This course places a heavy emphasis on designs favoring incremental data processing, enabling systems optimized to continuously ingest and analyze ever-growing data.
Databricks Class For Certified Associate Developer Exam: This course offers delegates a hands-on introduction to Databricks and may be used as an initial primer for the Databricks Certified Associate Developer exam.
Apache Spark™ Programming with Databricks: This course explores the fundamentals of Spark programming on the Databricks platform, including Spark architecture, the DataFrame API, basic query optimization, Structured Streaming, and Delta Lake.
Data Analysis with Databricks SQL: This course provides a comprehensive introduction to Databricks SQL. Students will write queries for data lakehouses, produce visualizations and dashboards, and set up automatic alerts for reporting to stakeholders.
Introduction to Python for Data Science & Data Engineering: This course is intended for complete beginners to Python to provide the basics of programmatically interacting with data using standard data manipulation and visualization libraries.
Optimizing Apache Spark on Databricks: This course helps experienced Apache Spark programmers understand the primary causes of Spark performance problems, use the Spark UI to identify root causes of performance issues, and apply mitigation techniques to increase performance and stability in Spark applications.
Scalable Machine Learning with Apache Spark: This course teaches the full scalable data science workflow using Apache Spark ML, including data cleaning and exploration, feature engineering, model training, and hyperparameter tuning. By the end of this course, you will have built an end-to-end distributed machine learning pipeline ready for production.
