Elastic Stack Mastery with Elasticsearch & AWS

EDUCBA via Coursera Specialization

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Overview

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This specialization provides a complete pathway to mastering the Elastic Stack—covering Elasticsearch, Logstash, Kibana, and AWS deployment. Learners will design scalable data models, construct complex queries, and visualize real-time insights. Through guided, project-based lessons, you’ll gain hands-on experience in cluster management, CI/CD automation, and Elastic Beanstalk deployments. By the end, learners will have built and optimized real-world data pipelines for analytics and monitoring across distributed cloud environments.

Syllabus

Course 1: Elasticsearch: Build, Query & Optimize with ELK
Course 2: Elasticsearch Joins & Parent-Child Queries
Course 3: AWS Elastic Beanstalk & CI/CD for Cloud Projects

Courses

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6 hours 5 minutes
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By the end of this course, learners will be able to configure development environments, implement version control with Git and AWS CodeCommit, automate deployments through CodePipeline, and deploy scalable applications using AWS Elastic Beanstalk. They will also apply advanced deployment strategies, integrate databases, and evaluate real-world case studies with APIs, data visualization, and filters. This course offers a step-by-step, project-driven approach to cloud deployment, making it ideal for learners who want both foundational knowledge and hands-on experience. Unlike theory-heavy programs, this curriculum emphasizes practical implementation through guided projects on flight monitoring during the COVID-19 pandemic, providing learners with industry-relevant skills. By completing this course, learners will build expertise in DevOps workflows, CI/CD automation, and cloud-native application deployment. They will be prepared to design, test, and scale applications effectively, while mastering the integration of real-time monitoring and visualization techniques. This unique blend of foundational concepts, advanced practices, and case studies ensures learners can confidently manage end-to-end cloud deployment projects in professional environments.
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6 hours 29 minutes
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By the end of this course, learners will be able to apply nested queries, implement parent-child mappings, and execute relational-style joins in Elasticsearch for advanced data modeling. You will gain the skills to index event-driven data, use inner hits for detailed matches, and optimize query performance with global ordinals. This course is designed to bridge the gap between traditional relational databases and Elasticsearch’s document-oriented model. Through practical workshops and structured lessons, learners will explore application-side joins, nested queries, and indexing best practices. The course then advances into modeling complex one-to-many relationships using parent-child queries, with hands-on exercises for has_child and has_parent functionalities. What makes this course unique is its step-by-step alignment of relational concepts with Elasticsearch capabilities, ensuring you not only understand the theory but also practice real-world applications. Whether you are a data engineer, developer, or search specialist, this course equips you with essential strategies to analyze, structure, and query large-scale datasets efficiently in Elasticsearch.
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16 hours
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By completing this course, learners will be able to design data models, configure clusters, build custom analyzers, and construct powerful queries in Elasticsearch. They will also master the use of Cluster, Indices, and Document APIs to manage distributed data efficiently. The course provides practical skills in configuring analyzers, avoiding split-brain issues, translating SQL queries into Elasticsearch DSL, and implementing advanced queries such as geo_point and geo_shape searches. This course benefits learners by bridging the gap between theory and hands-on application, enabling them to use Elasticsearch with Logstash and Kibana for real-time data ingestion, indexing, and visualization. Unlike traditional database training, this course emphasizes distributed architecture, near real-time search, and practical troubleshooting strategies. What makes this course unique is its comprehensive coverage of Elasticsearch fundamentals through to advanced APIs, combined with real-world scenarios that highlight scalability, performance optimization, and query precision. Whether you are a beginner in NoSQL systems or an IT professional aiming to go beyond basics, this course equips you with the knowledge and confidence to apply Elasticsearch effectively in modern data-driven environments.