Basic Knowledge in Machine Learning.

The course is an open online course, accessible via free registration, and participation is therefore based on the information provided by the participant upon registration. The course does not give university credits.

The MOOC includes six modules: Fundamentals of AI: A brief, beginner-level, non-technical introduction to AI, covering its fundamentals, history, branches, types, and applications. Fundamentals of ML : Overview, goal, its types, algorithms, and applications. Introduction to Data: About data, datafication, data preparation, and feature extraction, providing a foundation for understanding, processing, visualising, and extracting insights from data. Mathematics: Essential mathematics for machine learning, covering set theory, linear algebra, and calculus, and developing the ability to apply these concepts to ML problems. Statistics and Probability : Essential statistical and probability knowledge needed to understand and apply machine learning concepts to practical problems. Programming Language Python: Basic Python programming and essential libraries for storing, manipulating, analysing, and visualizing data for machine learning.