Data science courses

Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

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

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

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

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 essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

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

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

Enter the world of Alteryx Designer and learn how to navigate the tool to load, prepare, and aggregate data.

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

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

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

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

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

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

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

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

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

Prepare for your next coding interviews in Python.

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

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

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

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

Improve data literacy skills by analyzing remote working policies.

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

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

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

Master sampling to get more accurate statistics with less data.