Society and organizations are creating petabytes of data, and with Artificial Intelligence (AI) we can put that data to work in order to improve well-being, increase revenue and reduce costs.
Society and organizations are creating petabytes of data, and with Artificial Intelligence (AI) we can put that data to work in order to improve well-being, increase revenue and reduce costs. With modern technology we can use internal and external, structured and unstructured data and apply Artificial Intelligence to bring new possibilities to make predictions, improve decision making, improve company performance and augment human capabilities.
However, this new field of science comes with new terminologies and technologies. 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 organization for effective use of AI. That needs a vision to define the best opportunities for AI to support the business, it needs a framework to understand which capabilities in the organization have to improve, and an implementation strategy to know what to do where and when.
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, to create an AI strategy and develop an AI ready organization, to know how to set up and run an AI project and to assess the make or buy decision of tooling.
By the end of the course, participants will be able to:
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
Advanced Analytics vs Artificial Intelligence
Algorithms but without technical jargon
Data as fuel for AI
The data engineering platform
AI opportunity matrix
Ideation of AI projects
Running of AI projects
How to transform to an AI ready organization
AI and ethics