Artificial Intelligence

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.

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TN-512: Essential Business Analysis Course

Course Overview:

This course covers the key elements required to understand and apply business analysis techniques in an IT-centric business environment.  It identifies key best practices to deal with the challenges of eliciting, analyzing, and specifying project requirements.  The key material in each section of this course is reinforced with a student driven lab scenario allowing each participant hands-on practice with the key business analysis concepts that are introduced in this course. At the end of the focused sections on business analysis techniques, the students will engage in a student-driven business analysis case study blending all the learned techniques into a finished product. This course is approximately 60% lecture and  40% lab time.

Attendees to TN-512: Essential Business Analysis Course will receive TechNow approved course materials and expert instruction.

Dates/Locations:

No Events

Duration: 5 Days

Course Objectives:

  • Overview of Business Analysis Workshop
  • Eliciting Project Workshop
  • Case Study
  • Analyzing Requirements and Writing Case Studies
  • Case Study

Prerequisites:

  • None

 

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TN-430: Elasticsearch Engineer (ELK)

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.

 

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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

  • Write and execute a search query for terms and/or phrases in one or more fields of an index
  • Write and execute a search query that is a Boolean combination of multiple queries and filters
  • Write an asynchronous search
  • Write and execute metric and bucket aggregations
  • Write and execute aggregations that contain sub-aggregations
  • Write and execute a query that searches across multiple clusters
  • Write and execute a search that utilizes a runtime field

Developing Search Applications

  • Highlight the search terms in the response of a query
  • Sort the results of a query by a given set of requirements
  • Implement pagination of the results of a search query
  • Define and use index aliases
  • Define and use a search template

Data Processing

  • Define a mapping that satisfies a given set of requirements
  • Define and use a custom analyzer that satisfies a given set of requirements
  • Define and use multi-fields with different data types and/or analyzers
  • Use the Reindex API and Update By Query API to reindex and/or update documents
  • Define and use an ingest pipeline that satisfies a given set of requirements, including the use of Painless to modify documents
  •   Define runtime fields to retrieve custom values using Painless scripting

Cluster Management

  • Diagnose shard issues and repair a cluster’s health
  • Backup and restore a cluster and/or specific indices
  • Configure a snapshot to be searchable
  • Configure a cluster for cross-cluster search
  • Implement cross-cluster replication

 

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