This PySpark test evaluates candidates' proficiency in DataFrames and Spark SQL, Transformations and Actions, Machine Learning with MLlib, Data Sources and Formats, Streaming with Structured Streaming, Apache Spark Basics, PySpark Basics, Debugging and Troubleshooting, Performance Optimization, and Integration with Python Ecosystem.
This PySpark test assesses candidates' expertise in key areas such as DataFrames and Spark SQL, Transformations and Actions, Machine Learning with MLlib, Data Sources and Formats, Streaming with Structured Streaming, Apache Spark Basics, PySpark Basics, Debugging and Troubleshooting, Performance Optimization, and Integration with Python Ecosystem. It is designed to evaluate the ability to handle complex data processing tasks, optimize performance, and integrate PySpark with other Python tools, ensuring candidates can effectively manage and analyze large datasets.
This assessment is ideal for roles such as Data Engineers, Data Scientists, Big Data Developers, and Software Engineers who work with large-scale data processing and analytics using PySpark.
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Access to Objective Way of Assessments - MCQs, Checboxes, Fill in the blanks, Subjective (Manually Scored), File Upload (Manually Scored)
Access to Practice Way of Assessments - Programming, Debugging, Database, Data Science,
Access to Real-world, work like Assessments - Projects, DevOps, Machine Learning, Subjective (AI Evaluated), Video (Technical Knowledge), Video (Communication Skill), Whiteboarding (AI Evaluated)
Assessment Design consultation services according to Curriculum, Training or Learning Paths