Data science courses

This course dives deeper into the Azure's backbone by going into topics like containers, virtual machines and much more.

Learn to process, transform, and manipulate images at your will.

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

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

Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.

Learn how to translate business questions to well-formed analytical questions and select the right analytical solutions.

Discover modern data architecture's key components, from ingestion and serving to governance and orchestration.

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

Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces.

This course introduces dbt for data modeling, transformations, testing, and building documentation.

Learn about string manipulation and become a master at using regular expressions.

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

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.

Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.

Learn to write SQL queries to calculate key metrics that businesses use to measure performance.

Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.

This course focuses on feature engineering and machine learning for time series data.

Discover how to make better business decisions by applying practical data frameworks—no coding required.

Prepare for your next coding interviews in Python.

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

Learn how to clean data with Apache Spark in Python.

Create new features to improve the performance of your Machine Learning models.

Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAI's embedding model!

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

Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.

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

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

Learn to create your own Python packages to make your code easier to use and share with others.

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.