Data science courses

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

Gain a clear understanding of data privacy principles and how to implement privacy and security processes.

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

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

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

Dive into the Python ecosystem, discovering modules and packages along with how to write custom functions!

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

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

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

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

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

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

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

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

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

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

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

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

This introductory course on data culture provides an essential understanding of data culture concepts and their practical applications.

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

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

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

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

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

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

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

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