Elasticsearch is an open-source search and analytics engine designed for fast and scalable data exploration. As the demand for Elasticsearch professionals continues to grow, many online courses have emerged to provide comprehensive training on its usage and implementation. This article aims to list some of the best Elasticsearch courses available online, exploring their key features and benefits. Whether you are a beginner or an experienced developer looking to enhance your Elasticsearch skills, you will find valuable insights and resources to support your learning journey.
Here’s a look at the Best Elasticsearch Courses and Certifications Online and what they have to offer for you!
Complete Guide To Elasticsearch Online Course
- Complete Guide To Elasticsearch Online Course
- 1. Complete Guide to Elasticsearch by Bo Andersen (Udemy) (Our Best Pick)
- 2. Elasticsearch 8 and the Elastic Stack: In Depth and Hands On by Sundog Education by Frank Kane, Frank Kane, Coralogix Ltd., Sundog Education Team (Udemy)
- 3. Elasticsearch 8 and the Elastic Stack: In Depth and Hands On by Sundog Education by Frank Kane, Frank Kane, Coralogix Ltd., Sundog Education Team (Udemy)
- 4. ElasticSearch, LogStash, Kibana ELK #1 – Learn ElasticSearch by TetraNoodle Team, Manuj Aggarwal (Udemy)
- 5. Elasticsearch Masterclass [Incl., Elasticsearch 7 update] by Vinoth Parthasarathy (Udemy)
- 6. Using Elasticsearch and Kibana by Loony Corn (Udemy)
- 7. Elasticsearch in Action by Sezin Karli (Udemy)
- 8. The Complete Elasticsearch and Kibana Tutorial for beginners by Tutorial Drive (Udemy)
- 9. Building a Search Server with Elasticsearch by Packt Publishing (Udemy)
- 10. Complete ElasticSearch with LogStash, Hive, Pig, MR & Kibana by DataShark Academy (Udemy)
1. Complete Guide to Elasticsearch by Bo Andersen (Udemy) (Our Best Pick)
The Complete Guide to Elasticsearch is an online course that teaches Elasticsearch from scratch and covers the ELK stack (Elasticsearch, Logstash & Kibana) and Elastic Stack. The course is designed to equip learners with the necessary skills to become professionals in Elasticsearch in just a few hours. The tutorial is a combination of theory and practical exercises, allowing learners to gain a deep understanding of how Elasticsearch works under the hood.The course covers all the important aspects of Elasticsearch, starting from the absolute beginning, and does not require prior knowledge or experience with Elasticsearch. Upon completion, learners will be able to utilize Elasticsearch for various purposes, such as building a full-text search engine, data analytics for large amounts of data with aggregations, and using Elasticsearch as a time series database (TSDB).Combined with other products in the Elastic Stack, learners will be able to unlock several other features, such as log management and log analysis, observability, data visualization and reporting, and security analysis (SIEM).It should be noted that this course is intended for developers who want to interact with an Elasticsearch cluster and not for system administrators looking to maintain an Elasticsearch cluster in production. The course focuses on functionality relevant to utilizing the capabilities of Elasticsearch as a developer.The course does not cover Logstash and Kibana. However, the instructor offers other courses that cover these topics in greater detail. The course is dedicated solely to Elasticsearch and provides learners with an in-depth understanding of the topic. The course consists of several sections, including Introduction, Getting Started, Managing Documents, Mapping & Analysis, Introduction to Searching, Term Level Queries, Full Text Queries, Adding Boolean Logic to Queries, Joining Queries, Controlling Query Results, Aggregations, Improving Search Results, and Conclusion.
2. Elasticsearch 8 and the Elastic Stack: In Depth and Hands On by Sundog Education by Frank Kane, Frank Kane, Coralogix Ltd., Sundog Education Team (Udemy)
This course is titled Elasticsearch 8 and the Elastic Stack: In Depth and Hands On and is taught by Sundog Education by Frank Kane, Frank Kane, Coralogix Ltd., and the Sundog Education Team. The course provides a comprehensive tutorial on using Elasticsearch, Kibana, Logstash, and Beats to search, analyze, and visualize big data. Elasticsearch is a popular technology for powering search and analytics on big websites and is an important tool for managing massive data. The course covers everything from installation to operations and includes over 100 lectures with 15 hours of video.
The course covers how to set up search indices on an Elasticsearch 8 cluster and query data in various ways, including fuzzy searches, partial matches, search-as-you-type, pagination, and sorting. Each lesson includes hands-on examples using a virtual machine running Elasticsearch on the learner’s own PC. The course also explores what’s new in Elasticsearch 8 and illustrates all the new syntax requirements of Elasticsearch commands.
The course delves into the often-overlooked problem of importing data into an Elasticsearch index and covers various ways to get Elasticsearch started from large, existing data sets at scale. Learners will also learn how to stream data into Elasticsearch using Logstash and Filebeat. Additionally, the course covers Elasticsearch’s aggregation capabilities for structured data, allowing learners to bucket and analyze data and visualize it using Kibana and Kibana Lens.
Learners will also learn how to manage operations on their Elastic Stack, monitoring their cluster’s health, scaling up their cluster, and performing rolling restarts. The course includes instructions on spinning up Elasticsearch clusters in the cloud using Amazon Opensearch Service and the Elastic Cloud. Elasticsearch is positioning itself as a faster alternative to Hadoop, Spark, and Flink for many common data analysis requirements, and this course aims to help learners understand and use this important tool.
3. Elasticsearch 8 and the Elastic Stack: In Depth and Hands On by Sundog Education by Frank Kane, Frank Kane, Coralogix Ltd., Sundog Education Team (Udemy)
This course by Sundog Education and Coralogix Ltd. covers Elasticsearch 8 and the Elastic Stack, which are essential tools for managing large data sets. The course provides over 100 lectures, including 15 hours of video, on topics such as installation, search indexing, querying data, importing data, aggregation, and operations. The course also covers new features in Elasticsearch 8 and provides hands-on examples using a virtual machine. Additionally, the course shows how to use Kibana and the Elastic Stack’s web UI to visualize and analyze data. Finally, the course covers Elasticsearch in the cloud, specifically using Amazon OpenSearch Service and the Elastic Cloud.
4. ElasticSearch, LogStash, Kibana ELK #1 – Learn ElasticSearch by TetraNoodle Team, Manuj Aggarwal (Udemy)
The ElasticSearch, LogStash, Kibana ELK #1 – Learn ElasticSearch course offered by the TetraNoodle Team and Manuj Aggarwal focuses on the ElasticSearch enterprise search engine. This tool is one of the core components of the ELK stack, a framework capable of handling Big Data demands and scale. The ELK stack is widely used by diverse organizations and has an active community that develops and supports source code, components, plugins, and knowledge about these tools.
The course is structured to provide an overview of ELK and ElasticSearch technology, with an emphasis on enabling learners to run and operate their search clusters using these components. The course content is divided into sections such as Getting Started With ElasticSearch, ElasticSearch In Action, and Putting It All Together.
ELK and ElasticSearch skills are in high demand, and professionals with these skill sets reportedly earn annual salaries as high as $100,000. This course could be valuable for anyone seeking to advance their career in this field.
In summary, this course provides an opportunity to learn about the ElasticSearch enterprise search engine, one of the core components of the ELK stack. It covers the technology involved and aims to equip learners with the knowledge and skills needed to operate their search clusters using these tools.
The Elasticsearch Masterclass course, including Elasticsearch 7 update, is a comprehensive resource for learning the Elastic Stack, consisting of Elasticsearch, Logstash, and Kibana. The course is designed to teach students the skills necessary to handle large volumes of data as professional programmers. The course is structured to provide a balance of theory and implementation. The goal is to make Elasticsearch clear and easy to understand by diving deeply into relevant concepts and sharing knowledge helpful to programmers.
This interactive course is fun and exciting while still providing in-depth learning. Specifically, students will learn core principles of Elasticsearch and Apache Lucene, the secret behind Elasticsearch’s speed, how to perform real-time analytics on large data sets, and how to process data from numerous sources using Logstash. The instructor delivers the course at an excellent pace, transforming theoretical content into interactive lectures to make concepts clearer.
Students have access to full support and can ask questions seven days a week. The course comes with a 30-day full money-back guarantee, so students can enroll with confidence. The course is divided into several sections: Introduction, Dive into the Functionality, Inside Cluster, Search in Depth, Aggregation – Having Fun with Statistics, and Processing the Events in Logstash.
Student reviews of the course have been overwhelmingly positive, praising the instructor’s thorough explanations and use of examples and illustrations. Students appreciate the interactive lectures and clear explanations, making concepts more concrete and easier to remember. Overall, the Elasticsearch Masterclass course is an excellent resource for anyone interested in the field of Elasticsearch and big data.
The Using Elasticsearch and Kibana course, offered by Loony Corn, offers a comprehensive overview of Elasticsearch’s capabilities as both a search engine and data warehousing/BI technology. The course covers several key topics related to Elasticsearch as a search engine, including how search works, the use of inverted indices and relevance scoring, and horizontal scaling using sharding and replication. Additionally, the course delves into Elasticsearch’s use as a data warehouse/OLAP technology, focusing on Kibana for exploring data and finding insights. Other topics covered in the course include CRUD operations, aggregations, and Python client usage.
The course is divided into several sections, including an introduction to Elasticsearch and Elasticsearch’s Query DSL, which is used to perform powerful querying functions. Additionally, the course covers CRUD operations in Elasticsearch, which include Create, Retrieve, Update, and Delete operations. Aggregations, such as metrics, bucketing, and nested aggs, are also covered in the course. Lastly, Elasticsearch and Python are explored to demonstrate the use of Elasticsearch’s powerful capabilities in combination with Python.
Overall, the course aims to help learners use Elasticsearch’s search engine and data warehousing/BI technology. The course offers a practical approach to Elasticsearch’s capabilities, providing hands-on experience with REST APIs, Kibana, and Python client usage. By the end of the course, learners should have a solid understanding of Elasticsearch’s capabilities and how to harness its power to search, analyze, and visualize data.
The Elasticsearch in Action course, taught by Sezin Karli, is a hands-on course designed to teach students Elasticsearch from scratch. The course is suited for developers who want to learn about NoSQL databases or search servers, system administrators who are experts on relational databases but have no experience with new technologies, or anyone who wants to enhance their knowledge and career prospects. The course has been updated for Elasticsearch 2.0+.
Over 800 students have enrolled in the course and have left positive reviews. The course covers a wide range of topics, from real-time search and event management to sophisticated analytics and logging at scale.
The course is updated regularly to ensure that the content remains relevant to changes in Elasticsearch. It now includes a cheatsheet for the entire course, updated quizzes for better course coverage, and support for Elasticsearch 2.0+.
Students will start by learning the basics of Elasticsearch, including setting up their environment and launching their first node. They will then progress to operations such as Create/Read/Update/Delete, learn about mappings and analyzers, and master the essential part of searching documents in Elasticsearch. The course concludes with a chapter on sorting and relevance.
Students who enroll in the course will have lifetime access to the course content, as well as any updates. They will also have access to the instructor’s support through the discussions section.
This is a tutorial offered by Tutorial Drive that covers the basics of ElasticSearch and Kibana for developers and users. The aim of the course is to provide a quick start to these tools, without much theory. Upon completion, learners will know how to install ElasticSearch and Kibana, communicate with them, index and remove documents, perform basic operations like CRUD, compare ElasticSearch with other databases, search for documents, aggregate data, import real-time data, and plot visualizations and dashboards. The course takes 3-5 hours to complete and includes quizzes.
The course comprises several sections covering the essentials of ElasticSearch and Kibana. The ElasticSearch section introduces learners to the concepts and fundamentals of ElasticSearch, including installation, exploration of the cluster, indices, documents, APIs, data modification, bulk operations, query language, searches and queries, and aggregations. The Kibana section covers getting started with Kibana, importing real-time data, using Discover, creating visualizations, and creating dashboards. Additionally, there is a weekly topic and a bonus section.
The course material is provided, and the course is designed to be easily understood by everyone. The beginning lectures cover basic concepts, followed by advanced topics, and finally the use of the combination of ElasticSearch and Kibana.
The Building a Search Server with Elasticsearch course by Packt Publishing aims to provide learners with the necessary skills to develop a custom search application using Elasticsearch. The course covers a variety of topics, including the basics of Elasticsearch, client-side applications, field type classification, query types, filters, autocomplete, highlighting, deployment, and security. The course starts with an introduction to Elasticsearch and client-side applications. Learners will then learn about Elasticsearch’s automatic classification of field types and how to override them if necessary. The course also covers several query types provided by Elasticsearch for returning results for the AngularJS application. The course then moves on to adding filters or aggregations in Elasticsearch to enable users to narrow down their search results to a specific topic. Learners will also learn how to implement autocomplete and highlighting. Finally, the course concludes with an overview of deployment and security, ensuring that learners are equipped with the necessary tools to craft rich search interfaces that deliver great results to their users. The course instructor, Daniel Beach, is a search architect specializing in client-side application development, and has built search applications for publishers and government agencies. The course is divided into seven sections, namely Getting Started with Elasticsearch, Data Ingestion, Querying Elasticsearch, Connecting Elasticsearch to Our Application, The Advanced Search Functionality, Adding the Autocomplete Functionality, and Finishing Up.
The Complete ElasticSearch with LogStash, Hive, Pig, MR & Kibana course is offered by DataShark Academy and is suitable for beginners to advanced professionals. This course teaches how to use ElasticSearch with Apache Hadoop and build real-world big data applications.
Section 1 of the course focuses on Ingestion Flows (Hadoop to ElasticSearch) and covers four major topics, including installing Apache Hive and PIG, creating a MapReduce program, and moving data using LogStash into an ElasticSearch index.
Section 2 focuses on Egression Flows (ElasticSearch to Hadoop) and teaches how to load indexed data from an ElasticSearch cluster back into a Hadoop cluster. It covers four major topics, including importing ElasticSearch indexed data into Apache Hive, Hadoop, and LogStash.
Section 3 covers Data Visualization (Business Intelligence) and teaches how to use indexed data from an ElasticSearch cluster to create dynamic dashboards using Kibana.
Section 4 of the course teaches how to maintain an application in production, specifically monitoring an ElasticSearch cluster using Marvel plugins. Topics include cluster health monitoring and setting up a wait-for-trigger mechanism.
Section 5 teaches about the search capabilities offered by ElasticSearch and how to search something in real-time from an ElasticSearch index.
The course provides step-by-step instructions for installing required tools and components, and working code examples are provided for students to experiment with. Windows users will need to install a virtual machine to set up a single node Hadoop cluster. The course is divided into several sections covering building the foundation, setting up a working environment, building blocks of ElasticSearch, operations and queries, data pipelines, data visualization, monitoring an ElasticSearch cluster, and where to go from here.