Apache Spark Training
Apache Spark isn't just another framework - it's a game-changer in data processing. Imagine handling massive datasets up to 100x times faster than traditional methods, unlocking valuable real-time insights. Web Age's Spark training teaches basics and advanced topics like data analytics with PySpark.
This intensive hands-on Data Engineering training course teaches the students how to apply Python to the practical aspects of data engineering and introduces the students to the popular Python libraries used in the field, including NumPy, pandas, Matplotlib, scikit-learn, and Apache Spark.
Leverage the Apache Spark platform's massively parallel processing capabilities using PySpark, a Python-based language supported by Spark. Along with introducing PySpark, this course covers Spark Shell to interactively explore and manipulate data. Spark SQL is introduced for a uniform programming API to work with structured data. The course ends with covering Pandas for data manipulation and analysis and data visualization with seaborn.
This intensive hands-on training course teaches the participants the relevant parts of the (Azure) Databricks cloud platform to get them up to speed quickly and offers a unique opportunity to work with multiple programming languages and systems, including PySpark, SQL, and Scala to determine which language/system is best suited for which task at hand.
This Spark and Machine Learning training teaches participants how to build, deploy, and maintain powerful data-driven solutions using Spark and its associated technologies. The course begins with an introduction to Spark, its architecture, and how it fits into the Hadoop and Cloud-based ecosystems. Participants learn to set up Spark environments using DataBricks Cloud, AWS EMR clusters, and SageMaker Studio. In addition, students learn about Spark's core functionalities, including RDDs, DataFrames, transformations, and actions.
