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Apache Spark™ Programming with Databricks – Instructor Led Training
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.

Applied Data Engineering Solutions with Databricks – Instructor Led Training
This 2-day course is focused on helping users apply best practices when building a Lakehouse architecture on Databricks. Special emphasis is placed on Delta Lake, Structured Streaming, and data management.

Data Engineering with Databricks – Instructor Led Training
This 2-day course will teach 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, from raw data ingestion to consumption by end users.

Just Enough Python for Apache Spark™ – Instructor Led Training
This 1-day course aims to help participants with or without a programming background develop just enough experience with Python to begin using the Apache Spark programming APIs.

Machine Learning in Production – Instructor Led Training
In this 1-day course, machine learning engineers, data engineers, and data scientists learn the best practices for managing the complete machine learning lifecycle from experimentation and model management through various deployment modalities and production issues. Students begin with end-to-end reproducibility of machine learning models using MLflow including data management, experiment tracking, and model management before deploying models with batch, streaming, and real-time as well as addressing related monitoring, alerting, and CI/CD issues. Sample code accompanies all modules and theoretical concepts.

Optimizing Apache Spark™ on Databricks – Instructor Led Training
This 2-day course aims to deepen the knowledge of key “problem” areas in Apache Spark, how to mitigate those problems, and even explores new features in Spark 3 that further help to push the envelope in terms of application performance.

Scalable Deep Learning with TensorFlow and Apache Spark™ – Instructor Led Training
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.

Scalable Machine Learning with Apache Spark™ – Instructor Led Training
In this course, you will experience 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.