Cursos de datos, IA y nube

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Explore ways to work with date and time data in SQL Server for time series analysis

Practice data storytelling using real-world examples! Communicate complex insights effectively with a dataset of certified green businesses.

In this course, youll learn how to import and manage financial data in Python using various tools and sources.

Learn to work with Plain Old Java Objects, master the Collections Framework, and handle exceptions like a pro, with logging to back it all up!

Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Ensure high data quality in data science and data engineering workflows with Pythons Great Expectations library.

Visualize seasonality, trends and other patterns in your time series data.

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

Learn how to approach and win competitions on Kaggle.

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.

Learn how to use GPT tools responsibly and confidently. Discover how these tools work and techniques for writing prompts and evaluating outputs.

In this course youll learn to use and present logistic regression models for making predictions.

Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

Master Amazon Redshifts SQL, data management, optimization, and security.

Learn to build recommendation engines in Python using machine learning techniques.

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

Learn Databricks SQL for data engineering, analytics, and real-time data workflows in the lakehouse architecture.

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Learn how to efficiently collect and download data from any website using R.

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.