Purpose 

The purpose of the program is to provide an educational introduction to Machine Learning, starting from the basic prerequisite knowledge. Machine Learning is a highly demanded skill in the job market. The main goal of the program is to equip the learner with a solid foundation and a strong toolset for their professional development. This foundation includes acquiring basic skills such as computer programming and data preprocessing. The tools used to build these skills are the Python programming language and its scientific libraries, namely Numpy, Maplotlib, SciPy, and Pandas. Additionally, a solid mathematical background is also essential as it forms the basis for all Machine Learning Algorithms.

In the second part of the program, the trainees become familiar with two fundamental axes of the field: Supervised Learning and Unsupervised Learning. In Supervised Learning, algorithms are "trained" using data (input) for which their corresponding mappings to other data (output) are known, with the aim of predicting the outcomes of new, unknown data.

In Unsupervised Learning, algorithms are not "trained" but rather attempt to discover patterns or structures in data that are not explicitly linked to any specific conclusion.

Target group 

Graduates of Departments of Mathematics, Science or Engineering.

 Discount policy 

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