Machine learning is the process of developing and applying predictive algorithms to predicting future outcomes using available training data. Machine learning is a corner-stone for Data science, Big Data analytics, Robotics, Natural language processing and AI in general. Course introduces students to supervised and unsupervised machine learning concepts and algorithms from basic classification to Deep Learning with artificial neural networks. As computers and GPUs become more powerful, Deep Neural Networks are gradually taking over from simpler Machine Learning methods. The course does not require specific prior knowledge. Course outcomes are: The student will be able to describe and compare Machine Learning methods starting from legacy approaches to the state of the art Deep Neural Networks. The student will be able to recognize research problems and give examples for current solutions and tools for the design of the Machine Learning systems. The student will be able to apply Machine Learning methods to practical problems. The student will be able to give clear presentations about research and results. The course will give opportunity to participate in research projects with a potential eventually leading to the Master or Doctoral degree.