Arnaud Vuacheux

- Master programming applied to Data Science in Python. - Scrapping all kind of data. - Design relational databases and build advanced queries with SQL. - Study of mathematic concepts behind data science: statistics, probability and linear algebra. - Conduct advanced analysis with Jupyter notebook and Pandas + dataviz. - Implement Machine Learning supervised and unsupervised models with scikit-learn. - Deploy Machine Learning models in production with Google Cloud Platform. - Build and train fully connected deep neural networks to solve classification problems. - Use neural networks for object detection and recognition. - Best practices when working on a data science project within a tech team and Machine Learning preprocessing, training and testing, performance metrics, etc.