Planning AI Implementation


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

This 13-video course explores how artificial intelligence (AI) can be leveraged, how to plan an AI implementation from setup to architecture, and the issues surrounding incorporating it into an enterprise for machine learning. Learners will explore the three legs of AI: how it applies intelligence-like behavior to machines. You will then examine how machine learning adds to this intelligence-like behavior, and the next generation with deep learning. This course discusses strategies for implementation of AI, organizational challenges surrounding the adoption of AI, and the need for training of both personnel and machines. Next, learn the role of data and algorithms in AI implementation. Learners continue by examining several ways in which an organization can plan and develop AI capability; the elements organizations need to understand how to assess AI needs and tools; management challenges; and the impact on personnel. You will learn about pitfalls in using AI, and what to avoid. Finally, you will learn about data issues, data quality, training concepts, overfitting, and bias.



Expected Duration (hours)
0.8

Lesson Objectives

Planning AI Implementation

  • Course Overview
  • describe how adopting an AI strategy requires proper expectations and buy-in
  • specify the various organizational challenges surrounding the adoption of AI
  • describe personnel training and how an AI implementation requires training
  • describe the role that data and algorithms play in an organizational AI implementation
  • specify why AI is commonly misinterpreted as substitution for personnel and how it should be considered as a complement to personnel
  • describe the ways that an organization can plan and develop AI capability
  • describe the challenges facing management when developing an AI solution and how it can impact personnel
  • specify the pitfalls of AI and why they should be avoided
  • describe the common elements of an organizational AI strategy
  • specify the various issues surrounding data, data quality, and the concepts of training, overfitting, and bias
  • describe the elements organizations need to understand in order to assess AI needs and tools
  • discuss the various aspects of AI an organization needs to address to plan for AI
  • Course Number:
    it_mlpaitdj_01_enus

    Expertise Level
    Beginner