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Elastic Stack Mastery with Elasticsearch & AWS

EDUCBA via Coursera Specialization

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Details

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 10 hours a week
Sessions

Self-Paced
Level

Beginner

Found in

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

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Build practical cloud deployment and DevOps skills with AWS Elastic Beanstalk and CI/CD. You’ll begin by configuring a development environment and build files, then use Git and AWS CodeCommit for version control. You’ll automate reliable deployments with AWS CodePipeline and configure notifications to support a complete CI/CD workflow. Next, you’ll explore the core AWS Elastic Beanstalk workflow and learn to create, configure, deploy, and manage applications through its simplified PaaS framework. You’ll also apply deployment strategies, customize scaling, set policies, and integrate databases for persistent application data. Finally, you’ll connect these skills through a project-driven case study focused on flight monitoring during the COVID-19 pandemic. You’ll deploy an application that uses APIs, pie chart visualization, and filters to generate actionable insights. Designed for learners seeking foundational knowledge and hands-on experience in cloud deployment, this course uniquely combines guided implementation with an end-to-end case study. Enroll to confidently design, test, automate, deploy, and scale cloud applications using AWS Elastic Beanstalk, Git, CodeCommit, and CodePipeline.
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Build advanced Elasticsearch skills to model and query complex document relationships. You’ll begin by exploring how Elasticsearch supports relational-style querying through application-side joins and JSON structures. You’ll then apply nested queries, configure appropriate mappings, validate document structures, and accurately analyze arrays of objects. As you progress, you’ll index event-driven data such as sign-up and payment events, examine data flows, and use inner hits to retrieve detailed nested or child document matches. You’ll also construct parent-child mappings, use global ordinals, and evaluate performance trade-offs when modeling one-to-many relationships without duplicating data. Through structured lessons and practical workshops, you’ll implement has_child and has_parent queries, refine results with filters and constraints, and sort parent documents using child values. Designed for data engineers, developers, and search specialists, this course uniquely connects familiar relational concepts with Elasticsearch’s document-oriented model. Enroll to confidently structure, index, and query complex datasets while making informed decisions about nested and parent-child approaches.
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Build practical Elasticsearch skills and learn to create, query, and manage distributed search solutions with the ELK Stack. You’ll begin by exploring NoSQL fundamentals and the core architecture of Elasticsearch, including clusters, nodes, indices, documents, mappings, and data types. Using Kibana Dev Tools, you’ll interact with Elasticsearch and test queries in real time. You’ll then examine how character filters, tokenizers, and token filters process text, and implement edge n-gram and synonym analyzers to improve search relevance and autocomplete. You’ll also configure cluster discovery and gateway settings to improve stability and prevent split-brain issues. As you progress, you’ll distinguish query and filter contexts and build match, term-level, range, prefix, geo_point, and geo_shape queries. You’ll use Cluster, Indices, Document, and Bulk APIs to monitor cluster health, manage shards and aliases, and perform efficient CRUD operations. Designed for beginners in NoSQL and IT professionals ready to advance their search expertise, this course uniquely connects distributed architecture, near real-time search, query precision, and practical troubleshooting. You’ll also understand how Elasticsearch works with Logstash and Kibana for real-time data ingestion, indexing, and visualization. Enroll to develop applicable skills for scalable, data-driven environments.