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Home » Technology » Big Data & Data Science » Using Artificial Intelligence on the Microsoft Platform

Course Skill Level:

Foundational to Intermediate

Course Duration:

3 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    Big Data & Data Science

  • Course Code:

    UAIMSPL21E09

Who should attend & recommended skills:

Developers, project leads, & project managers

Who should attend & recommended skills

  • Developers, project leads, project managers
  • Executives and managers should attend the Overview

About this course

“This course gives developers practical skills of dealing with todays massive volumes of data, drawing conclusions from this data, and feeding it back in the application, thus providing a better user experience.

Skills acquired & topics covered

  • Handling massive amounts of data
  • Drawing conclusions from the data
  • Application data feedback

Course breakdown / modules

  • Insufficiency of Structured Data
  • Manual Processing
  • Evolution of Textual Analytic Technology

  • Taxonomy Components
  • Taxonomies and Language

  • Hierarchical Taxonomies
  • Networked Taxonomies
  • More Applications of Taxonomies

  • Curated Taxonomies
  • Building Your Own Taxonomy
  • Qualifying the Nouns

  • MoveRemove Processing
  • Taxonomy Customization
  • Word Pairs
  • Transporting the Taxonomy

  • Types of Textual Data
  • Types of Textual Dat

  • Document Fracturing
  • Named Value Processing
  • Supporting Processes

  • Basic Refinements
  • Custom Variables
  • Inline Contextualization
  • Proximity Analysis and Resolution
  • Stop Word Processing
  • Associative Word Processing
  • Homographic Resolution
  • Alternate Spelling
  • Acronym Resolution
  • Stemming
  • Date Normalization

  • Sentiment Analysis
  • Negativity Analysis
  • Medical Records

  • Publicly Available Banking Data
  • Comments Collected
  • Textual Disambiguation
  • Secondary Inference Analysis
  • Visualization
  • Interpreting the Dashboard
  • Considering a Single Bank

  • What the Call Center Hears
  • Processing the Narrative
  • Examining the Dashboard
  • Getting to Visualization

  • Voice of the Customer
  • Analyzing Restaurant Feedback

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