Artificial Intelligence (AI) | Transforming Business with New Technologies

Artificial Intelligence (AI) revolution is the development of computer systems that can perform tasks normally requiring human intelligence. When you encounter awe-inspiring technology, it can be challenging to see how you can apply it to your own business. You need a framework and language to ask deeper, sharper questions and find the right strategy.

This five-day Artificial Intelligence training course has been designed to develop the insight of the participants on Data Science. Participants on this EuroMaTech training course will learn how to build Artificial Intelligence, and to optimize the Artificial Intelligence to reach its maximum potential. EuroMaTech training modules will enable the participants to understand the theory of Artificial Intelligence and help them to understand how to solve real-world problems with Artificial Intelligence.

Participants attending Artificial Intelligence training course will develop the following competencies:

• Understanding of the value of Artificial Intelligence and different algorithms
• Knowledge on how to analyze daily business problems and create Artificial Intelligence solutions
• Deeper understanding of the latest innovative technologies and apply them to business

TRAINING OBJECTIVES

By completing this EuroMaTech training course, the candidates will:

• Learn how Artificial Intelligence can be optimized so that maximum potential could be obtained
• Learn how the codes are generated and combined and what these code lines mean
• Understand the procedure of building the Artificial Intelligence
• Learn how to build Artificial Intelligence that is adaptable to any environment in real life
• Be able to identify potential areas of applications of Artificial Intelligence
• Obtain basic ideas and techniques in the design of intelligent computer systems
• Learn Statistical and decision-theoretic modelling paradigm
• Know how to build agents that exhibit reasoning and learning
• Be able to apply regression, classification, clustering, retrieval, recommender systems, and deep learning