Explainable AI (XAI) and Trustworthy AI are the
solutions that experts and managers seek to enhance the reliability of AI
systems and understand their complex decisions. Making AI decisions
understandable, and ensuring that AI systems are transparent, robust, and
respect data privacy.

 Enhance decision understanding:  

Make AI decision-making clear and
understandable, in addition to identifying the foundations of understanding AI
models of data and decisions.  

Build customer trust:  

Develop techniques that contribute to building
trust between the company and its customers through clear explanations of how
the decisions approved by AI systems are made.  

Ensure monitoring and control:  

Address and mitigate biases in AI models
through tools and methods to ensure accurate monitoring of models and maintain
quality performance.  

Deal with risks:  

Understand and analyze potential risks to
mitigate the challenges and risks resulting from AI, and ensure that AI systems
operate reliably under different conditions.   

 This course is ideal for multiple categories
within companies seeking to promote AI technologies transparently, as it is
designed to provide participants with the knowledge and skills necessary to
create AI solutions that meet the highest standards of ethical and responsible
AI: 

Technology and Innovation Managers 

Data Scientists and AI Engineers 

Operations Managers 

Compliance and Ethics Teams 

AI Consultants and Data Analysts  

 By the end of the course, your
understanding of Explainable AI (XAI) and Trustworthy AI capabilities will
change profoundly and raise your skills to an advanced level in terms of: 

Gain the skill of analyzing and
understanding how AI models make decisions and the ability to simplify complex
concepts for end users 

Gain skills that are in high
demand in the current job market and enhance the competitiveness of your employees
in the field of AI development 

Gain a deeper understanding of how
algorithms and the decision-making process work, as well as develop safer AI
solutions that take into account ethical and social aspects 

Build bridges of communication
with multidisciplinary teams and enhance effective communication between
developers and end users  

 1- Basic knowledge of AI and Machine Learning 

2- Experience in programming languages ​​(Python/R) 

3- Basic understanding of statistics and mathematics 

4- Knowledge of data science fundamentals