The "Essentials of Data Visualization using MS-Excel" certificate is a training course that introduces participants to the fundamental techniques of visual representation of data using Microsoft Excel software. It emphasizes the importance of transforming raw data into clear and relevant graphs to facilitate understanding and decision-making. The program covers essential Excel tools such as dynamic charts, pivot tables, charts, and advanced formatting options. Learners learn how to choose the right chart type for each dataset, highlight trends, and communicate results effectively. Intended for students, professionals, or anyone who wants to improve their data analysis and presentation skills, this certificate provides a practical mastery of Excel's visualization features. It provides a solid foundation for moving towards more advanced skills in business intelligence and data analytics.

The "Introduction to Energy and Environment" certificate is a training course that introduces participants to fundamental issues related to energy and the environment. It addresses the different sources of energy, whether fossil or renewable, and analyzes their impact on society and the planet. The programme highlights current issues such as climate change, pollution, sustainable resource management and energy efficiency. It also proposes a reflection on possible solutions, including the integration of renewable energies, the circular economy and environmental policies. Intended for students, professionals or anyone interested in the energy transition and sustainable development, this certificate allows students to acquire a solid general culture and an understanding of the links between energy, society and the environment. It is a useful basis for enriching an academic or professional career and can serve as a springboard to more specialised training in the field of energy and the environment.

The certificate “Basics of Machine Learning Algorithms” is designed to provide learners with a foundational understanding of how machines can be trained to recognize patterns and make predictions from data. It introduces the core concepts of supervised, unsupervised, and reinforcement learning, explaining how each approach works and where it is applied. Participants explore common algorithms such as linear regression, logistic regression, decision trees, k-nearest neighbors, support vector machines, naive Bayes, k-means clustering, and neural networks. The program emphasizes the workflow of machine learning, including data collection, preprocessing, model training, evaluation, and deployment. By completing this certificate, learners gain essential skills to analyze datasets, select appropriate algorithms, and build simple predictive models. It is intended for students, professionals, or anyone interested in artificial intelligence and data science, serving as a strong entry point into more advanced studies or practical applications in the field of machine learning.