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.

MS-10175: Developing & Customizing Applications for Microsoft SharePoint 2010 & 2013

Course Overview:

TechNow’s Course provides existing .NET developers with practical information and labs that enables them to build solutions on the Microsoft SharePoint 2010/2013 platform.

Attendees to MS-10175: Developing & Customizing Applications for Microsoft SharePoint 2010/2013 will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Duration: 5 days

Course Objectives:

Introduction to SharePoint 2010/2013 Development Platform
Using SharePoint 2010/2013 Developer Tools
Developing SharePoint 2010/2013 Web Parts
Working with SharePoint Objects on the Server
Creating Event Receivers and Application Settings
Developing Solutions by Using Business Connectivity Services
Developing SharePoint 2010/2013 Workflows
Working with Client-based APIs for SharePoint 2010/2013
Developing Interactive User Interfaces
Developing Silverlight Applications for SharePoint
Developing Sandboxed Solutions
Working with SharePoint Server Profiles and Taxonomy APIs
Developing Content Management Solutions

Prerequisites:

An understanding of the problem-solving techniques that apply to software development
Approximately 12 months experience with ASP .NET 3.5 with Visual Studio 2008 (or later)
Approximately 1 month development experience with SharePoint 2007 or SharePoint 2010/2013 and VS2010/2013 (includes beta releases) creating code that interacts with the SharePoint Sever-side APIs
Experience performing end user tasks with SharePoint 2007 or SharePoint 2010/2013 and an understanding of the purpose and use of the following:
- Lists
- Documents and Libraries
- Personalizing an SP Page/Site
- Using MySites
- Using SharePoint Designer

Comments

Latest comments from students

User: kelleyd10

Instructor comments: Clay was / is an outstanding instructor. He was very flexible in what the class needed. He was very accommodating and resourceful in answering the class questions. Clay's teaching style is greatly appreciated.

Facilities comments: Were good

User: dennij

Instructor comments: Very professional and knowledgeable. Available before and after class.

Facilities comments: Location was nice but too far from Lackland.

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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.

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