Due to rapid technological advancements, the foundation of AI solutions for decision-making, "Supervised" ML models, is now more accessible to practitioners. Mastering the most critical predictive models has become more accessible, especially with the improvement of automation tools.

It is common to have data sets with multiple variables describing business topics. But how can we extract all the hidden patterns from such complex data sets? Reducing the number of variables into simple "maps" with PCA becomes essential to highlight invisible relations within the data, facilitating the correct actions to take. This workshop also explains the difference between scientific market "clustering" and simple common sense "filtering". It empowers the definition of market niches and profiles them using Data Analysis techniques. Additionally, the program covers illustrations that reveal associations between the components of multiple variables for efficient tracking of pattern evolution. The workshop also includes practical applications with two different technologies, allowing participants to become more like consultants than mere experts.

 The "Reinforcement Learning in Practice" training is an in-depth, hands-on workshop designed to equip participants with the knowledge and practical skills needed to effectively implement Reinforcement Learning (RL) techniques. Over three days, attendees will explore the fundamental principles of RL, understand key algorithms, and apply them to real-world problems. This workshop blends theoretical insights with coding exercises and case studies, ensuring participants gain conceptual clarity and practical experience building RL models.