Artificial Intelligence (AI) Strategy for Business Professionals

About the Course

Name: Artificial Intelligence (AI) Strategy for Business Professionals

Code:

Sectors: Live/Online Class

  Date   Days   Venue   Fees
26 - 28 Oct 2021 3 Live Online Classroom $550 BOOK NOW

Introduction

In the race of companies and businesses in reaching a competitive advantage as well as cost and time savings through Artificial Intelligence (AI), the technology is continuously changing industry processes and capabilities. AI presents a compelling opportunity for industries whose operations span the virtual and physical worlds.

This training course is designed to provide participants with the technical foundations and principles of AI in order to become an AI leader in their organizations. This will help them understand AI concepts and use cases, converse on a qualified level with the data specialists, create an AI strategy and develop an AI ready organization, run an AI project, and assess the make or buy decision of tooling.

Objectives

At the end of the training course, participants will be able to:

  • Gain a comprehensive understanding of AI as a concept and all its applications
  • Discuss on a qualified level with business and data specialists on relevant topics 
  • Design and implement an AI strategy and develop an AI ready organization 
  • Identify and use the different AI applications in the business value chain 
  • Learn and apply best practices in an AI project with its activities 
  • Assess the available and necessary skills and competencies

Training Methodology

This training course is designed to be highly interactive and participatory. To ensure maximum comprehension and retention, this training will utilize a variety of proven virtual learning methods such as break-out sessions for group discussions and brainstorming, virtual icebreakers, recorded videos, case studies, and readings.

Outline

Day 01

  • Introduction to Artificial Intelligence (AI), Machine Learning (ML) and Data Science
  • AI in historical setting and combinatorial technologies 
  • Introduction to AI, concepts, narrow and general AI 
  • Different types of AI 
  • AI - sense, reason, act 
  • The thinking in AI: Machine learning
  • Advanced Analytics vs Artificial Intelligence 
  • Looking back, now, forward 
  • 4 types of data analytics 
  • Analytics value chain
  • Algorithms but without technical jargon 
  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning

Day 02

  • Data as fuel for AI 
  • Structured and unstructured data 
  • The 5 V’s of data
  • Data governance
  • The data engineering platform 
  • Just enough to understand the data architecture 
  • Big data reference architecture 
  • 3 categories of data usage
  • AI opportunity matrix 
  • Successful use cases by Porter’s value chain
  • Primary activities
  • Supporting activities
  • Successful use cases by technology 
  • NLP 
  • Image recognition 
  • Machine learning
  • Ideation of AI projects 
  • AI Funnel process 
  • Several idea generation approaches
  • Prioritize projects 
  • AI project canvas

Day 03

  • Running of AI projects
  • Machine learning life cycle 
  • AI machine learning canvas 
  • When to make and when to buy AI solutions 
  • How to transform to an AI ready organization 
  • Use the AI strategy cycle
  • Dimensions of the AI framework 
  • Practical approach to assess the AI maturity of the organization 
  • Best organizational structures
  • Benefits of an AI Center of Excellence
  • Skills and competencies
  • AI and ethics 
  • Risks of AI 
  • Ethical guidelines
  • Realizing trustworthy AI

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