Training schedule
IN-COMPANY TRAINING PROGRAMS
Contact Giovanni Lanzani, if you want to know more about custom data & AI training for your teams. He’ll be happy to help you!
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Data Science with Spark Training
Apache Spark is a powerful open-source processing engine built around speed, ease of use, and advanced analytics. Through our experienced consultants, you can learn to unlock its full potential and master this challenging tool yourself via our Data Science with Spark training.
“I liked every aspect of this training and would like to thank the trainers. They did an excellent job of explaining how to use Spark for data science. This is the fourth GoDataDriven training I’ve followed. All were great, but this was the best one so far.” —Data Scientist, Knab
Clients we've helped
What you'll learn
Spark basics
- Spark execution
- SparkSession
- Transformations vs. actions
- Laziness and lineage: how Spark optimizes code
- How to use the Spark UI
- Advanced Spark
- How to apply partitioning and how Spark reads and writes data
- Shuffling, narrow wide operations, and their impact on performance
- The catalyst optimizer
- About scheduling and job execution
- About caching and persistence levels
DataFrames
- The basic concepts
- All about Spark DataFrames and pandas DataFrames
- How to load and save DataFrames
- The functions API
- How to join data
- User-defined functions and pandas’ user-defined functions (with performance implications)
- Window operations
Spark.ml
- Machine Learning with Spark
- Pre-processing data and feature engineering
- Model selection
- Pipeline API
- Advanced topics
Spark structured streaming
- Structured streaming
- Machine Learning & streaming
- Sources and sink
- Windows & aggregations
- Checkpointing & watermarking
- Fault tolerance & Kafka
- Kafka as a source and as a sink
The schedule
- Spark basics
- Advanced Spark
- DataFrames
- Window functions
- Spark.ml
- Spark structured streaming
- Integrating Apache Spark with Apache Kafka