Introduction to Portfolio Risk Management in Python
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Siga videos cortos dirigidos por instructores expertos y luego practique lo que ha aprendido con ejercicios interactivos en su navegador.
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Aprende a hacer predicciones con Apache Spark usando árboles de decisión, regresión logística y más.
Learn to perform linear and logistic regression with multiple explanatory variables.
Domina NoSQL y mejora los flujos de datos. Aprende Snowflake, Postgres JSON y Redis.
Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.
Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.
Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
Practice Power BI with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Learn about ARIMA models in Python and become an expert in time series analysis.
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
This course will show you how to integrate spatial data into your Python Data Science workflow.
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.
Utiliza las herramientas avanzadas de visualización de Seaborn para crear visualizaciones hermosas e informativas.
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Aprende sobre la gestión del riesgo, el valor en riesgo y mucho más aplicado a la crisis financiera de 2008 utilizando Python.
Aprende sobre LLMOps desde la idea hasta la implementación y cómo aplicarlo a tus aplicaciones.
Visualize seasonality, trends and other patterns in your time series data.
Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!