Quantitative Risk Management in R
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
Assista a vídeos curtos apresentados por instrutores especializados e depois pratique o que aprendeu com exercícios interativos em seu navegador.
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Ao continuar, você aceita nossos Termos de Uso, nossa Política de Privacidade e que seus dados serão armazenados nos EUA.Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
Automatize a manipulação de dados com a KNIME, dominando a mesclagem, a agregação, os fluxos de trabalho de banco de dados e o manuseio avançado de arquivos.
Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.
Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.
Aprenda a criar visualizações de dados atraentes com o KNIME, incluindo gráficos, componentes e painéis.
Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.
Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.
Learn how to prepare and organize your data for predictive analytics.
Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.
Elevate your analysis with this hands-on course using SQL with DataLab workbooks.
Master AI for marketing to plan smarter campaigns, create quality content, and build custom AI agents.
Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.
Learn how to visualize big data in R using ggplot2 and trelliscopejs.
Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.
Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.