Workshop

Masterclass AI for Business managers

Basta Group /   (NL)

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Society and organizations are creating petabytes of data, and with Artificial Intelligence (AI) we can put that data to work in order to increase revenue and reduce costs. With modern technology we can use internal and external, structured and unstructured data and algorithms to improve or automate decision making with better predictions and augment human capabilities.

However, this new field of science comes with new technologies and terminologies. But It is not just about data and technology. To really create business value with AI you need to scale up from isolated Proof of Concepts to a coherent approach and prepare the organisation for effective use of AI. Our 4 pillars approach helps with initiating, guiding and scaling AI.

A vision and strategy to define the best opportunities for AI to support the business, a framework to understand which capabilities in the organisation have to improve, and a Center of Excellence for coordination and education.

This course provides participants with the AI literacy to be the business AI leader in their organizations, to understand AI concepts and use cases, to converse on a qualified level with the data specialists about projects, to create an AI strategy and develop an AI ready organisation, to know how to set up and run an AI project and to assess the make or buy decision of tooling.

Class Methodology
This class can apply a variety of interactions, ranging from team work on case studies, to individual work on applying templates to their own experience, to group discussions about joint challenges, all depending on available time.

Class Objectives
By the end of this course, participants will be able to, in nontechnical terms,

  • Explain AI as a concept and its applications
  • Understand and identify the different AI applications in the business value chain
  • Recognize the technologies and algorithms behind AI
  • Apply best practices in an AI project with its activities
  • Assess the available and necessary skills and competencies
  • Discuss on a qualified level with business and data specialists on relevant topics
  • Create and execute an AI strategy and develop an AI ready organisation

Target Audience
This course is designed for senior, middle and high potential management who recognize that digital transformation and AI is unavoidable; and for those who understand that continuous improvement, innovation and disruption is part of doing business and want to be prepared and reap the benefits of Artificial Intelligence.

In short, this course is for managers wanting to identify what AI can do for them and to drive Digital Transformation, rather than understand the technical methodologies of what happens underneath its hood.

Understanding of technology concepts such as machine learning, algorithms, data and cloud is helpful but not required.

Course Outline

1 Artificial Intelligence in context

  • AI in historical setting and combination of technologies
  • Introduction to AI, concepts, narrow and general AI
  • AI: sense, reason, act
  • The thinking in AI: Machine learning

2 Advanced Analytics vs Artificial Intelligence

  • Looking back – now – forward
  • 4 types of data analytics
  • Analytics value chain

3 Introduction to Algorithms (without technical jargon)

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning

4 Data as fuel for AI

  • Structured and unstructured data
  • The 5 V’s of data
  • 6 domains of Data management

5 The data engineering platform

  • Understand the data architecture
  • Tooling, Languages and API’s
  • Big data reference architecture
  • 3 categories of data usage

6 AI opportunity matrix

  • Successful use cases by Porter’s value chain
    • Primary activities:
    • Supporting activities
  • Successful use cases by technology
    • Natural Language Processing
    • Image recognition
    • Text mining
    • Predictive analytics

 7 Ideation of AI projects

  • AI Funnel proces
  • Several Idea generation approaches
  • Prioritize projects
  • AI project canvas

8 Running of AI projects

  • Machine learning life cycle, MLops
  • AI machine learning canvas
  • Make or Buy decisions of AI solutions

9 Pillars to create value with AI in the organisation

  • AI strategy cycle explained
  • 10 capabilities of the AI framework
  • Practical approach to assess the AI maturity of the organisation
  • Best organisational structures
  • Benefits of an AI Center of Excellence
  • Skills and competencies

10 AI and ethics

  • Risks of AI
  • Explainable AI (XAI), Fair AI (FAI)
  • Ethical guidelines, EU framework
  • Realising trustworthy AI
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