The Complete Big Data & Machine Learning Bundle

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10 Courses & 68 Hours
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What's Included

Elasticsearch & The Elastic Stack: In-Depth and Hands-On
  • Certification included
  • Experience level required: Intermediate
  • Access 96 lectures & 8 hours of content 24/7
  • Length of time users can access this course: Lifetime

Course Curriculum

96 Lessons (8h)

  • Your First Program

  • Installing and Understanding Elasticsearch

    Section 1 Intro0:44
    Installing Elasticsearch17:35
    Elasticsearch Overview5:44
    Intro to HTTP and RESTful API's11:48
    Elasticsearch Basics: Logical Concepts1:58
    Term Frequency / Inverse Document Frequency3:48
    Using Elasticsearch3:59
    What's New in Elasticsearch 73:41
    How Elasticsearch Scales7:27
    Quiz: Elasticsearch Concepts and Architecture4:08
    Section 1 Wrapup0:30
  • Mapping and Indexing Data

    Section 2 Intro0:36
    Connecting to your Cluster7:03
    Getting to Know the Movielens Data Set3:53
    Analyzers8:27
    Import a Single Movie via JSON / REST10:25
    Insert Many Movies at Once5:29
    Updating Data in Elasticsearch6:28
    Deleting Data in Elasticsearch2:15
    Insert, Update, and Delete a Fictitious Movie4:14
    Dealing With Concurrency10:20
    Using Analyzers and Tokenizers10:47
    Data Modeling with Elasticsearch, Pt 15:24
    Data Modeling with Elasticsearch, Pt 27:00
    Section 2 Wrapup0:23
  • Searching with Elasticsearch

    Section 3 Intro0:29
    Using Query-String Search8:05
    Using JSON Search10:13
    Phrase Matching6:21
    Querying in Different Ways4:25
    Pagination6:18
    Sorting7:54
    More with Filters3:34
    Using Filters2:39
    Fuzzy Queries6:05
    Partial Matching5:30
    Query-time Search as you Type4:00
    N-Grams, Part 15:16
    N-Grams, Part 28:11
    Section 3 Wrapup0:20
  • Importing Data Into Your Index - Big or Small

    Section 4 Intro0:50
    Importing Data from Scripts8:16
    Importing with Client Libraries6:35
    Importing with a Script Exercise3:55
    Logstash Overview4:50
    Installing Logstash8:57
    Running Logstash5:11
    Importing Data from MySQL using Logstash, Part 17:55
    Importing Data from MySQL using Logstash, Part 27:47
    Importing Data from AWS S3 using Logstash7:55
    Integrating Kafka with Elasticsearch, Part 15:58
    Integrating Kafka with Elasticsearch, Part 26:02
    Elasticsearch and Apache Spark, Part 18:20
    Elasticsearch and Apache Spark, Part 25:58
    Import Movie Ratings from Spark to Elasticsearch8:48
    Section 4 Wrapup0:36
  • Aggregation

    Section 5 Intro0:59
    Aggregations, Buckets and Metrics10:13
    Histograms7:39
    Aggregating Time Series Data6:03
    Generating Histogram Data4:21
    Nested Aggregations, Part 16:03
    Nested Aggregations, Part 28:45
    Section 5 Wrapup0:23
  • Using Kibana

    Section 6 Intro0:20
    Installing Kibana4:37
    Analyzing Shakespeare with Kibana10:06
    Exploring Data with Kibana3:19
    Section 6 Wrapup0:21
  • Analyzing Log Data with the Elastic Stack

    Section 7 Intro0:31
    FileBeat and the Elastic Stack Architecture7:33
    X-Pack Security3:10
    Install, Configure, and Use FileBeat5:58
    Analyzing Server Logs with Kibana9:52
    Log Analysis with Kibana5:25
    Section 7 Wrapup0:31
  • Elasticsearch Operations

    Section 8 Intro0:39
    How Many Shards Should I Use?5:09
    Scaling with New Indices4:02
    Index Alias Rotation3:52
    Index Lifecycle Management2:09
    Choosing Your Hardware3:17
    Heap Sizing3:14
    Monitoring6:25
    Elasticsearch SQL5:30
    Practicing Failover, Part 17:12
    Practicing Failover, Part 28:46
    Snapshots9:51
    Rolling Restarts6:39
    Section 8 Wrapup0:29
  • Elasticsearch in the Cloud

    Section 9 Intro0:58
    Using Amazon Elasticsearch Service, Part 17:20
    Using Amazon Elasticsearch Service, Part 25:32
    Using Elastic Cloud9:48
    Section 9 Wrapup0:11
  • You Made It!

    I Made It! Now What?3:54

Elasticsearch & The Elastic Stack: In-Depth and Hands-On

FK
Frank Kane

Frank Kane | Founder, Sundog Education

4.5/5 Instructor Rating: ★ ★ ★ ★

Frank Kane spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaching others about big data analysis.

324,714 Total Students
77,009 Reviews

Description

Elasticsearch is a powerful tool not only for powering search on big websites but also for analyzing big data sets in a matter of milliseconds. It's an increasingly popular technology, and a valuable skill to have in today's job market. This comprehensive course covers it all, from installation to operations, with 60 lectures including 8 hours of video. Elasticsearch is positioning itself to be a much faster alternative to Hadoop, Spark, and Flink for many common data analysis requirements. It's an important tool to understand, and it's easy to use! Dive in and see what it's all about.

1,814 positive ratings from 11,737 students enrolled

  • Access 96 lectures & 8 hours of content 24/7
  • Set up search indices on an Elasticsearch cluster & querying that data in many ways
  • Import data into an Elasticsearch index
  • Stream data into Elasticsearch using Logstash & Filebeat
  • Bucket & analyze data & visualize it using the Elastic Stack's web UI, Kibana
  • Manage operations on your Elastic Stack using X-Pack to monitor your cluster's health

"The course is detailed and very well structured. It provides necessary insights and kick-starts your experience with the elastic stack." – Deepanshu Galyan

Specs

Important Details

  • Length of time users can access this course: lifetime
  • Access options: web & mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Updates included
  • Experience level required: intermediate

Requirements

  • Some familiarity with web services and REST
  • Some familiarity with Linux will be helpful
  • Exposure to JSON-formatted data will help

Terms

  • Unredeemed licenses can be returned for store credit within 30 days of purchase. Once your license is redeemed, all sales are final.