Cursos de ciência de dados

Learn how to use Python to analyze customer churn and build a model to predict it.

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

Develop the skills you need to clean raw data and transform it into accurate insights.

Learn to streamline your machine learning workflows with tidymodels.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Learn how to load, transform, and transcribe speech from raw audio files in Python.

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Learn how to design and implement triggers in SQL Server using real-world examples.

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Learn how to visualize time series in R, then practice with a stock-picking case study.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

In this course youll learn how to perform inference using linear models.

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Learn how to build a model to automatically classify items in a school budget.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Learn how to pull character strings apart, put them back together and use the stringr package.

In this course youll learn how to leverage statistical techniques for working with categorical data.

Learn efficient techniques in pandas to optimize your Python code.

Learn to use the Census API to work with demographic and socioeconomic data.

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.