Cloudera Data Engineering: Developing Applications with Apache Spark Course
- Duration: 32 hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
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Course Overview
The Cloudera Data Engineering: Developing Applications with Apache Spark course is designed to equip data engineers, ETL developers, and analytics professionals with the skills to design, develop, and optimize scalable data applications using Apache Spark on the Cloudera Data Platform (CDP). Participants will gain hands-on experience in building Spark applications that process large volumes of data, performing transformations, aggregations, and integrations with other data sources. The course emphasizes best practices in Spark programming, performance tuning, resource management, and real-world use cases to prepare data engineering teams for production-grade workloads.
Course Details
- Master core Apache Spark concepts and distributed data processing
- Hands-on experience developing Spark applications using Scala and/or Python
- Ability to optimize data pipelines for performance and resource efficiency
- Expertise in working with structured and unstructured data at scale
- Skills to integrate Spark with the CDP ecosystem and data sources
- Readiness for enterprise-level data engineering challenges
- Open to data engineers, software developers, ETL specialists, and analytics professionals
- Ideal for individuals responsible for building scalable data pipelines and applications
- Basic understanding of programming (Python/Scala), SQL, and distributed systems is recommended
- Familiarity with big data concepts and cluster environments is beneficial
- Corporate sponsorship or group participation is encouraged
- Learn how to write efficient Spark applications to process large datasets
- Gain expertise in Spark RDDs, DataFrames, and optimized transformations
- Understand methods for Spark performance tuning and debugging
- Develop skills in integrating Spark applications with data stores and messaging systems
- Master advanced Spark features such as streaming, machine learning, and graph processing
- Achieve readiness for real-world data engineering responsibilities
- Introduction to Apache Spark Architecture
- Spark Programming with Scala and Python
- Working with DataFrames & Spark SQL
- Deploying Spark Applications on CDP
- Performance Tuning & Optimization
- Advanced Transformations & Actions
- Spark Streaming & Real-Time Data Processing
- Spark Machine Learning & MLlib
- Integration with Data Sources & CDP Ecosystem
- Hands-On Labs and Practical Projects
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