Data science courses

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

Learn to combine data from multiple tables by joining data together using pandas.

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

Learn how to explore whats available in a database: the tables, relationships between them, and data stored in them.

Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.

Learn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch.

Improve your Python data importing skills and learn to work with web and API data.

Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

This course will take you from Snowflakes foundational architecture to mastering advanced SnowSQL techniques.

Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.

This introductory and conceptual course will help you understand the fundamentals of data warehousing.

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

Discover modern data architectures key components, from ingestion and serving to governance and orchestration.

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

Dive deep into the principles and best practices of prompt engineering to leverage powerful language models like ChatGPT to solve real-world problems.

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

Learn to build effective, performant, and reliable data pipelines using Extract, Transform, and Load principles.

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

Discover how to build AI-powered applications using LLMs, prompts, chains, and agents in LangChain.

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

You’ll learn how to (un)pivot, transpose, append and join tables. Gain power with custom columns, M language, and the Advanced Editor.

Learn how to analyze a SQL table and report insights to management.

Data Analysis Expressions (DAX) allow you to take your Power BI skills to the next level by writing custom functions.

Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.