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.

Data Engineering with Python
Course ID: WA2905
Delivery: On-Site or Instructor-led Virtual

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.

Advanced Data Analytics with PySpark
Course ID: WA2936
Delivery: On-Site or Instructor-led Virtual

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.

Data Engineering Bootcamp Training using Python and PySpark
Course ID: WA3020
Delivery: On-Site or Instructor-led Virtual

This hands-on Data Engineering Bootcamp teaches attendees the foundations of data engineering using Python and Spark SQL. Students learn how to build production-ready data-driven solutions and gain a comprehensive understanding of data engineering.
Intermediate Data Engineering with Python
Course ID: WA3032
Delivery: On-Site or Instructor-led Virtual

This fast-paced two-day Data Engineering training course focuses on data analytics through the use of the Python language, the Spark platform for highly scalable operations, and AWS Glue for comprehensive data access. Extensive hands-on exercises are provided to ensure that students get the practical experience required to perform successfully.
Programming on Azure Databricks with PySpark, SQL, and Scala
Course ID: WA3208
Delivery: On-Site or Instructor-led Virtual

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.

Spark and Machine Learning at Scale
Course ID: WA3290
Delivery: On-Site or Instructor-led Virtual

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.

Building Batch Data Analytics Solutions on AWS
Delivery: On-Site or Instructor-led Virtual

In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR.
Implementing a Data Analytics Solution with Azure Databricks
Course ID: DP-3011
Delivery: On-Site or Instructor-led Virtual

Learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run data analytics workloads in a data lakehouse. This learning path helps prepare you for Exam DP-203: Data Engineering on Microsoft Azure.
Implementing a Machine Learning Solution with Azure Databricks
Course ID: DP-3014
Delivery: On-Site or Instructor-led Virtual

Azure Databricks is a cloud-scale platform for data analytics and machine learning. Data scientists and machine learning engineers can use Azure Databricks to implement machine learning solutions at scale.