Instructor-led Training

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Advanced Data Engineering with Databricks (2 days)

This course delves into the advanced patterns, and practices for creating a scalable Lakehouse, including architecture, change data capture, incremental data updates, privacy, security, and production deployment. Prerequisites are strictly enforced.

Apache Spark™ Programming with Databricks (2 days)

This course uses a case study driven approach to explore the fundamentals of Spark Programming with Databricks, including Spark architecture, the DataFrame API, query optimization, Structured Streaming, and Delta.

Data Analysis with Databricks SQL (1 day)

This course provides a comprehensive introduction to Databricks SQL. Learners will ingest data, write queries, produce visualizations and dashboards, and learn how to connect Databricks SQL to Databricks Partner tools.

Data Engineering with Databricks (2 days)

This course teaches you best practices for using Databricks to build data pipelines, through lectures and hands-on labs. 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.

Deep Learning with Databricks (2 days)

This course covers the fundamentals of neural networks with TensorFlow and how to scale training, inference, and hyperparameter tuning of deep learning models with Apache Spark.

Introduction to Python for Data Science & Data Engineering (2 days)

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.

Machine Learning in Production (1 day)

This course covers the best practices for managing the complete machine learning lifecycle from experimentation and model management. Students will explore various deployment paradigms and CI/CD framework, and learn how to address production issues.

Optimizing Apache Spark™ on Databricks (2 days)

This course aims to deepen the knowledge of key optimization areas in Apache Spark and how to leverage them for performance boost.

Scalable Machine Learning with Apache Spark™ (2 days)

This course teaches the full data science workflow, including data exploration, feature engineering, model building, and hyperparameter tuning. By the end of this course, you will have built an end-to-end distributed machine learning pipeline ready for production.

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