Cursos de dados, IA e nuvem

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

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

Saiba como trabalhar com dados em tempo real usando tecnologias sem servidor na AWS.

Use as sofisticadas ferramentas de visualização do Seaborn para criar visualizações bonitas e informativas com facilidade.

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

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

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

Entenda os desafios de monitorar modelos de ML em produção, como desvio de dados e de conceito, e métodos para evitar a degradação do modelo.

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Using Python and NumPy, learn the most fundamental financial concepts.

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.

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

Learn how to detect fraud using Python.

Analyze text data in R using the tidy framework.

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

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

Learn to manipulate and analyze flexibly structured data with MongoDB.