Elasticsearch 8 and the Elastic Stack: In-Depth and Hands-On

Packt via Coursera Specialization

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Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 10 hours a week
Sessions

Self-Paced
Level

Beginner

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Overview

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This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this specialization, you will learn Elasticsearch’s role in the Elastic Stack and how to install, configure, and manage it for data search and analytics. You’ll discover how Elasticsearch powers search engines and analytics and gain proficiency in interacting with it through APIs, creating indices, and managing data. The first section covers Elasticsearch installation and basic concepts like term frequency, indices, and documents. You’ll also learn HTTP and RESTful APIs for interacting with Elasticsearch, and apply these skills through exercises like indexing movie data. As you progress, you’ll explore scaling Elasticsearch, optimizing queries, and using Kibana for data visualization. You’ll also learn to handle large datasets, perform log analysis, and manage Elasticsearch in the cloud. Designed for learners in data science, software development, and cloud technologies, this specialization is perfect for those looking to work with big data and enhance search engine capabilities. By the end of the specialization, you’ll be able to install, configure, and manage Elasticsearch clusters, scale data, and integrate with tools like Logstash, Kibana, and Kafka for cloud-based deployments.

Syllabus

Course 1: Foundations of Elasticsearch
Course 2: Learn Data Integration and Visualization with Elasticsearch
Course 3: Advanced Elasticsearch Operations and Cloud Deployment

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This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Dive deep into the advanced capabilities of Elasticsearch with this comprehensive course focused on operations and cloud deployment. Beginning with log data analysis, you’ll explore how to leverage the full power of the Elastic Stack, including FileBeat and Kibana dashboards. You'll also gain a thorough understanding of X-Pack security, ensuring your Elasticsearch environment is secure and resilient. The course then shifts focus to core Elasticsearch operations, covering crucial topics such as shard management, index lifecycle management, and performance monitoring. You’ll learn how to scale your Elasticsearch setup by adding indices, manage snapshots effectively, and troubleshoot common issues. Real-world exercises will reinforce these concepts, preparing you to handle the operational challenges of maintaining a large-scale Elasticsearch environment. In the final sections, you’ll master cloud deployment, an essential skill for modern infrastructure management. You'll explore the Amazon Elasticsearch Service and Elastic Cloud, understanding how to deploy, manage, and monitor Elasticsearch clusters in the cloud. This course is designed for experienced data engineers, system administrators, and cloud architects who are looking to advance their Elasticsearch skills. A solid foundation in Elasticsearch basics and general knowledge of cloud services is recommended. By the end of this course, you’ll be equipped with the knowledge to optimize and deploy Elasticsearch in any environment, making you an invaluable asset to your team.
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This course now features Coursera Coach — your interactive learning companion that helps you test your knowledge, challenge assumptions, and deepen your understanding as you progress. Unlock the power of Elasticsearch, one of the most widely used engines for search and analytics in modern, data-driven systems. Designed for data engineers, developers, and IT professionals, this hands-on course will take you from foundational concepts to building scalable, real-world search solutions with confidence. You’ll begin by setting up your Elasticsearch environment and learning how to interact with clusters using RESTful APIs. Through step-by-step guidance, you’ll build a solid grounding in how Elasticsearch stores, structures, and retrieves data at scale. As you progress, you’ll dive into mapping and indexing, working with real datasets such as MovieLens to practice connecting to clusters, importing data, and tailoring analyzers and tokenizers to your needs. You’ll also learn how to manage bulk operations and handle concurrency—skills essential for production-grade search systems. In the final modules, you’ll master Elasticsearch’s powerful search capabilities. You’ll explore fuzzy matching, partial searches, pagination, sorting, and filters, empowering you to design fast, precise, and flexible query experiences. By the end of this course, you will have: - Understood how Elasticsearch stores, indexes, and retrieves data. - Worked with real-world datasets to create and manage indexes. - Designed analyzers, tokenizers, and mappings for optimized search behavior. - Performed efficient bulk operations and addressed concurrency challenges. - Built flexible, performant searches using fuzzy queries, filters, sorting, and pagination. - Gained the confidence to implement and scale Elasticsearch solutions in real environments. A basic understanding of databases and data structures is helpful but not required — this course begins with fundamentals and guides you all the way to advanced techniques.
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This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course offers an in-depth exploration of data integration and visualization using Elasticsearch, Logstash, and Kibana, providing you with the tools and knowledge needed to manage and present complex data. The journey begins with understanding how to import data into Elasticsearch, whether it’s small-scale data or large datasets. You'll learn to use scripts, client libraries, and Logstash for data import, with practical exercises to reinforce your understanding. The use of Logstash is thoroughly covered, including working with various data formats and integrating data from MySQL, S3, and Kafka. As the course progresses, you'll dive into the world of data aggregation within Elasticsearch. You will explore concepts like buckets, metrics, and histograms, which are essential for analyzing and summarizing data. Through hands-on exercises, you'll learn how to effectively use aggregations to generate meaningful insights from time series data and nested data structures, ensuring that you can extract the maximum value from your data. In the final sections, the course shifts focus to visualization, teaching you how to harness the power of Kibana to create compelling, interactive dashboards. You'll start by installing and configuring Kibana, followed by an exploration of its core features, such as Kibana Lens and Canvas. These tools will enable you to visualize data in a way that is both informative and visually appealing, making your data presentations stand out. This course is designed for data engineers, analysts, and IT professionals who need to integrate, manage, and visualize data using Elasticsearch and Kibana. A basic understanding of databases and data structures is recommended to fully benefit from the course. By the end of the course, you'll have a solid foundation in data integration, aggregation, and visualization, empowering you to transform raw data into actionable insights.