Artificial Intelligence (AI) Strategy for Business Professionals - Virtual Learning

Course Objectives

Artificial Intelligence (AI) Strategy for Business Professionals - Virtual Learning

Course Objectives
By the end of the course, participants will be able to:

Explain AI as a concept and all its applications
Apply the different AI applications in the business value chain
Demonstrate 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 organization
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 basic technology concepts such as data and cloud is helpful but not required.

Target Competencies
AI Best Practice Application
AI Change Management
AI Business Translator
AI Project Management

Course Outline

Introduction to Artificial Intelligence (AI), Machine Learning (ML) and Data ScienceAI in historical setting and combinatorial technologiesIntroduction to AI, concepts, narrow and general AIDifferent types of AIAI - sense, reason, actThe thinking in AI: Machine learning
Advanced Analytics vs Artificial IntelligenceLooking back, now, forward4 types of data analyticsAnalytics value chain
Algorithms but without technical jargonSupervised learningUnsupervised learningReinforcement learning
Data as fuel for AIStructured and unstructured dataThe 5 V’s of dataData governance
The data engineering platformJust enough to understand the data architectureBig data reference architecture3 categories of data usage
AI opportunity matrixSuccessful use cases by Porter’s value chainPrimary activitiesSupporting activitiesSuccessful use cases by technologyNLPImage recognitionMachine learning
Ideation of AI projectsAI Funnel processSeveral idea generation approachesPrioritize projectsAI project canvas
Running of AI projectsMachine learning life cycleAI machine learning canvasWhen to make and when to buy AI solutions
How to transform to an AI ready organizationUse the AI strategy cycleDimensions of the AI frameworkPractical approach to assess the AI maturity of the organizationBest organizational structuresBenefits of an AI Center of ExcellenceSkills and competencies
AI and ethicsRisks of AIEthical guidelinesRealizing trustworthy AI

Per participant


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