TechNow has been training IT, programming, and Cyber Security for over 28 years. Artificial Intelligence skills are being developed across many enterprises.
Here is our list of Artificial Intelligence and Machine Learning related courses.
DoD 8570 Training in San Antonio, TX.
TechNow has developed a proven training program that brings the skillset to the certification process. TechNow is a mobile testing center that can deliver D0D 8570 training and the certification in one week. Our intergrated DoD 8570 training in San Antonio, TX incorporates hands on skills with testing objectives that produces an incredibly high pass rate. To learn more about our DoD 8570 training program click here
TechNow has heard many students talk about virtualized/remote training that TechNow Does Not Do. While training our most recent offering of PA-215: Palo Alto Networks Firewall Essentials FastTrack a student told his story of how he endend up in our course. His story we have heard for other technologies like Cisco, VMware, BlueCoat and other products.
A large percentage of training is moving to the virtualized/remote lab environments. Students are asked to use some variant of remote access software and remote into the training company's lab environment. Our student in our Palo Alto Networks Firewall course informed us that he went to a very costly offering of that course from the vendor and was not able to perform any labs. There were either network connectivity issues, or issues with the remote access software, or other problems. The whole training experience was very frustrating and not productive.
We keep our labs open to students if they would like after hours, or before hours access. Repeatedly going through a lab engrains that knowledge for later recall. Touching hardware is so critical in understanding the problems that arise when a cable comes loose, or a cable gets plugged in the wrong port. There are other scenarios such as just pulling the power cable, or turning off a power strip, or accidently overwriting a configuration. These disaster scenarious requires hands-on physical access to hardware. Preventing and recovering from disasters is what it's all about, and that requires hands-on, instructor led, real hardware.
Course Overview:
Getting started with the Elastic Stack (ELK), optimizing search performance and building efficient clusters. Ingest and process data, writing complex search requests and response utilization, scaling of clusters up or down, managing indices in large clusters and multiple clusters, management of clusters and troubleshooting recommendations.
Attendees to TN-430: Elasticsearch Engineer (ELK) will receive TechNow approved course materials, expert instruction, and prepare you to take ELK exam.
Dates/Locations:
No Events
Duration: 5 Days
Course Outline:
Data Management
- Define an index that satisfies a given set of requirements
- Define and use an index template for a given pattern that satisfies a given set of requirements
- Define and use a dynamic template that satisfies a given set of requirements
- Define an Index Lifecycle Management policy for a time-series index
- Define an index template that creates a new data stream
Searching Data
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Write and execute a search query for terms and/or phrases in one or more fields of an index
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Write and execute a search query that is a Boolean combination of multiple queries and filters
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Write an asynchronous search
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Write and execute metric and bucket aggregations
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Write and execute aggregations that contain sub-aggregations
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Write and execute a query that searches across multiple clusters
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Write and execute a search that utilizes a runtime field
Developing Search Applications
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Highlight the search terms in the response of a query
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Sort the results of a query by a given set of requirements
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Implement pagination of the results of a search query
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Define and use index aliases
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Define and use a search template
Data Processing
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Define a mapping that satisfies a given set of requirements
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Define and use a custom analyzer that satisfies a given set of requirements
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Define and use multi-fields with different data types and/or analyzers
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Use the Reindex API and Update By Query API to reindex and/or update documents
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Define and use an ingest pipeline that satisfies a given set of requirements, including the use of Painless to modify documents
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Define runtime fields to retrieve custom values using Painless scripting
Cluster Management
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Diagnose shard issues and repair a cluster’s health
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Backup and restore a cluster and/or specific indices
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Configure a snapshot to be searchable
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Configure a cluster for cross-cluster search
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Implement cross-cluster replication
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