Cursos de dados, IA e nuvem

Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.

Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

Conquiste o NoSQL e otimize fluxos de dados. Aprenda Snowflake para big data, Postgres JSON para documentos e Redis para chave-valor.

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

Learn how to clean data with Apache Spark in Python.

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

Discover how Marketing Analysts use data to understand customers and drive business growth.

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Explore Azure services like Compute, Storage, and Automation, with hands-on experience.

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Learn the core techniques necessary to extract meaningful insights from time series data.

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Aprenda a fazer previsões com Apache Spark usando árvores de decisão, regressões e pipelines.

Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.

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

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.

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.

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

Prepare for your next coding interviews in Python.

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