Read more here
Artificial Intelligence (AI) for Business Professionals
DATE
21 - 23 Oct, 2024
LOCATION
To Be Determined;
Why Attend?
Artificial Intelligence (AI) for Business Professionals
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.
- 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
- 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
- Successful use cases by Porter’s value chain
- Ideation of AI projects
- AI Funnel process
- Several idea generation approaches
- Prioritize projects
- AI project canvas
- 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
Join Our Community