Data science courses

Take your Power BI visualizations up a level with the skills you already have. Learn alternative data storytelling techniques to simply building dashboards.

Understand the fundamentals of Machine Learning and how it's applied in the business world.

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

Learn how to use GitHub's various features, navigate the interface and perform everyday collaborative tasks.

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

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

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

Learn to clean data as quickly and accurately as possible to help your business move from raw data to awesome insights.

Discover the different ways you can enhance your Power BI data importing skills.

In this course you will learn the details of linear classifiers like logistic regression and SVM.

Learn to use Google Sheets to clean, analyze, and draw insights from data. Discover how to sort, filter, and use VLOOKUP to combine data.

In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.

Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.

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

Learn the role Generative Artificial Intelligence plays today and will play in the future in a business environment.

Explore Excel Power Query for advanced data transformation and cleansing to boost your decision-making and analysis.

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

Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.

Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.

Gain an introduction to data governance, exploring its meaning, purpose, and how to implement a data governance framework.

In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

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

Enhance your reports with trend analysis techniques such as time series, decomposition trees, and key influencers.

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

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

Continue your data visualization journey where you'll learn practical techniques for incorporating DAX measures and progressive disclosure in your reports.

Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.

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

Transform almost any dataset into a tidy format to make analysis easier.

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.