NL AIC AI For Business and Government Courseware
Samenvatting
AI For Business and Government is a standard for all professionals.
'AI For Business and Government' is a certification that can be obtained after passing the corresponding exam.
This can be best be achieved by participating in an AI For Business training course.
This course is aimed at generic professionals working in business or government who do not necessarily have much experience with AI, or data or IT in general. However, they do want to understand what AI is, how it can benefit or affect their business environment and how they can leverage this to their advantage.
Topics covered include the benefits of AI applications, data management for AI, building and assessing an AI application, ethics, risks and reliability, and organizational success factors for enabling humans and machines to work together.
‘Where does Data Management end and AI application begin?’
The subjects covered are enumerated below, and are addressed in the course from a management perspective:
1. The applications and benefits of AI
2. Data, robots and definition of AI
3. Predictions, algorithms, machine and deep learning
4. Build and review an AI application
5. Data management for AI
6. Ethics and trustworthiness
7. Organizational success factors for helping man and machine to work together
8. The future of AI
This certificate was established by the Netherlands AI Coalition (NL AIC) as a standard for professionals who want to use Artificial Intelligence (AI) in their work environment and managers who need to decide on the general application and/or use of AI. A professional will learn what AI could mean for an organization and how to organize, implement and execute it. As a result, the exam is very application-oriented.
Trefwoorden
kunstmatige intelligentie ai bedrijven overheid certificering courseware training onderwijs management data management machine learning ethiek digitale transformatie algoritmes robotica technologie innovatie implementatie risicomanagement strategie organisatieontwikkeling professionals besluitvorming deep learning samenwerking automatisering efficiency competenties verandering
Trefwoorden
Specificaties
Inhoudsopgave
U kunt van deze inhoudsopgave een PDF downloaden
Agenda 9
Introduction (1) 13
Applications of AI and their Benefits (3) 14
History of Artificial Intelligence (6) 15
Definition of intelligence (12) 18
Different application areas and benefits of AI (18) 21
The fourth industrial revolution (26) 25
Data driven organizations (28) 26
Data, Robots and Artificial Intelligence (30) 27
AI and smart devices (33) 29
The robotic paradigm (37) 31
Types of agents (38) 31
Characteristics of intelligent agents (44) 34
Relationship between intelligent agents and machine learning (48) 36
Predictions, Algorithms, Machine and Deep Learning (50) 37
Data analytics (43) 39
Common types of problems (74) 49
Required fundamentals for data science (84) 54
Types of machine learning (101) 63
Common algorithms and techniques (110) 67
How Organizations Build and Assess AI Applications (125) 75
Goals & Tasks of building an AI application – high level overview (128) 76
A way to do so: CRISP-DM (130) 77
Key tools (142) 83
Evaluating and assessing AI applications (147) 86
Organizing your AI project team (150) 87
Managing Data for AI (154) 89
What is data? (157) 91
An overview of different responsibilities (166) 95
Ethics, Risks and Trustworthiness (179) 102
Ethical dilemmas and limitations of AI (182) 103
Societal concerns and objections to the use of AI (185) 105
EU ethical guidelines for trustworthy AI (187) 106
Importance of transparency and explainable AI (192) 108
Human and Machine Coexistence (194) 109
Different levels of AI (197) 111
Collaboration between humans and AI (203) 114
Key competencies of working with AI (207) 116
The Future Developments of AI (210) 117
General direction of where AI might go (213) 119
Examples of the future of AI (214) 119
Practice exams info 124
Syllabus 125
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