Data science courses

Navigate and use the extensive repository of models and datasets available on the Hugging Face Hub.

Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.

Prepare for your next coding interviews in Python.

You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.

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

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

Build the foundation you need to think statistically and to speak the language of your data.

Learn how to clean data with Apache Spark in Python.

Learn about Large Language Models (LLMs) and how they are reshaping the business world.

Discover how to become a data defender and keep data safe and secure with this beginner-friendly interactive course.

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

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

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

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

Take your R skills up a notch by learning to write efficient, reusable functions.

Improve data literacy skills by analyzing remote working policies.

Explore the latest techniques for running the Llama LLM locally, fine-tuning it, and integrating it within your stack.

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

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

Learn to perform linear and logistic regression with multiple explanatory variables.

Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

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

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.

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