Learn how to build a search engine and break into big data by mastering Elasticsearch 6, Kibana and Logstash (ELK stack)
What you’ll learn
- Build an Elasticsearch 6 cluster from scratch
- Perform various searches using the query DSL
- Perform powerful realtime analytics using the Aggregations DSL
- Combine Filters, Queries and Aggregations and understand document relevancy and searching
- The desire to learn a popular Big Data Technology
- Understand how to use an internet browser
LAST UPDATED Jan, 2020 – Elasticsearch Version 6
Elasticsearch is the biggest player in the big-data space since Hadoop. I would actually vouch that it’s the Hadoop killer!
It’s just now beginning to gain recognition and wider adoption in the no-sql big-data space and Elasticsearch has come a long way since it’s first release. I’m sure that by just adding Elasticsearch on your linkedin profile your going to gain the attention of various companies investing in this technology. So get excited about Elasticsearch because it is a big deal. The average salary for an Elasticsearch engineer is over $100,000 and the demand for engineers is high.
This course is most suited for people that want to not only power-up their resume with this new and exciting technology but also powerup their applications to be blazing fast by implementing Elasticsearch correctly. I’ve designed this course to be practical and easy to follow by repeating key concepts with step by step instructions and best practices for building a search Engine from scratch.
By the end of this course you’ll know everything there is to know about how to build a search engine using the most recent and popular version of Elasticsearch 6 for your application as well as how to perform powerful realtime analytics on your data.
With over 20,000 student and a 4.4 star rating, this is a Udemy best seller course with thousands of students who have benefitted from the content.
Don’t just take it from me, take it from the students that have taken this course.
★★★★★ Here’s reviews from real students that took this course ★★★★★
★★★★★ This is an awesome Masterclass. It provides all the basics to work with the ELK-Stack and gives a deep look in how the core Elasticsearch is working and how to use it.
Thanks to some sketches he explains the structure behind the programs. Here he might use a tablet to make his drawings as professional as the rest of the course. Thanks for the great help.
★★★★★ Instructor explains topics concisely and in depth. He provides resources that you can visit while watching the lectures to get better understanding of the topics he discusses. In addition, he encourages students to do some examples (challenges) that will solidify their understanding of the topics discussed in the course so far.
★★★★★ The teacher is very clear and he explains with simplicity easy and difficult concepts
★★★★★ Walked me through step by step in one lesson. I now have Kibana and Elasticsearch running locally. Awesome..
★★★★★ The instructor is very detailed and goes at pace that is easy to manage and follow along without adding excessive length to the course.
★★★★★ Highly recommended for the people who wants to understand the eleastic seach . I am very happy with the course. When I started I had no idea about the subject but now i’m feeling confident about it. Imtiaz teaching style is great. You will simply love it.
Topics covered in this course:
- Setting up Elaticsearch and Kibana
- Downloading and Configuring Logstash
- Indexing, Retrieving and Deleting Documents
- Text Analysis
- Index Settings
- Index Mapping
- Searching DSL Query Context
- Searching DSL Filter Context
- Aggregations DSL
- Indexing Apache Application Logs
- Kibana Visualizations
- Using Filebeat
- Older Elasticsearch 5 Material
There is a 30 day money back guarantee, so if you’re not satisfied for any reason, you get your money back no questions asked!
Who this course is for:
- Anyone who wants to learn how to build a search engine using Elasticsearch 6.0
Created by Imtiaz Ahmad
Last updated 8/2019
English [Auto-generated], French [Auto-generated], 6 more
Size: 4.30 GB