Quantitative Risk Management in R
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
Master GitHub Copilot to understand, write, and refine code with context, customization, and smart features.
Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.
Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.
Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.
In this course youll learn how to leverage statistical techniques for working with categorical data.
Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.
Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.
Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.
Are you curious about the inner workings of the models that are behind products like Google Translate?
Learn to easily summarize and manipulate lists using the purrr package.
Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.
Learn to process sensitive information with privacy-preserving techniques.
Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.
Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.
Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.
Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.
In this course youll learn how to apply machine learning in the HR domain.
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.
You will use Net Revenue Management techniques in Google Sheets for a Fast Moving Consumer Goods company.
Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.
GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.
Learn how to visualize time series in R, then practice with a stock-picking case study.
Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.