. "Artificial Intelligence"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Machine learning"@en . . "6" . "Machine learning language environments (PyTorch, TensorFlow, Keras, SciKit-Learn,\nNumPy). Linear and nonlinear regression, polynomial curve fitting, and classification. Bias-\nvariance trade-off. Radial basis functions. Neural networks. Activation functions, optimization\nalgorithms. Cross-validation, regularization, bootstrap. Convolutional neural networks and\nvisual data analysis. Batch-normalization, Dropout. Pre-trained models. Transfer learning.\nDetection of the objects by U-Net type networks. Recurrent neural networks in series\nanalyses. Generative adversarial neural networks." . . "Presential"@en . "FALSE" . . "Master in Astrophysics"@en . . "https://international.uni.wroc.pl/en/admission-full-degree-studies/programmes-english/astrophysics" . "no data" . "Presential"@en . "The program comprises only a few mandatory courses that acquaint you with general foundations of astrophysics, necessary computer simulation tools and data analysis methods, as well as selected observational techniques. This is supplemented by a wide range of elective courses enabling you to deepen your knowledge and skills according to your scientific interest. You can follow astronomy- or physics-oriented study track that will prepare you for the Master project held in the Astronomical Institute or the Institute of Theoretical Physics, respectively.\nIn the course of becoming an educated astrophysicist, you will gain expertize in mathematical modeling, computer simulations and advanced data analysis. You will also develop universal research competencies, including analytical and critical thinking, rigorous evidence-based reasoning, creativity and complex problem solving, active learning, as well as communication and teamwork skills."@en . . . . "2"@en . "TRUE" . . "Master"@en . "no data" . "1000.00" . "Euro"@en . "2150" . "no data" . "The modern job market awaits people with your competencies! Upon graduation, you will be capable of working in academy, R&D institutes and centers of education, as well as in various knowledge-based economy branches, including ICT, high-tech industry or financial institutions. However, you will be particularly well-prepared to undertake PhD studies and continue scientific career."@en . "no data" . "TRUE" . "Upstream"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .