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The course begins with what makes data big and how its insights can be applied, then moves into the processing tools themselves. You get hands-on work with Apache Hadoop and Apache Spark, along with Hive for querying.
Learners who already understand data basics and want to get their hands on distributed tools are the intended audience. Engineers exploring IBM Cloud or container-based deployment will also find the skills list relevant.
Because the course is self-paced, you can schedule the labs around other commitments and return to them as needed.
Skills you'll gain: Apache Hadoop, Apache Spark, Apache Hive, Big Data, IBM Cloud, Kubernetes, Docker (Software), Scalability, Data Processing, Development Environment, Distributed Computing, Performance Tuning, Application Deployment, Debugging.
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Data Engineering, Big Data, and Machine Learning on GCP
