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Popular in live online training
See allJuly 18, 2022
Python and R for Data Science
Presented by Boyan Angelov
Tackle complex data projects with the best of both worlds Bilingual people tend to think in concepts rather than words. This allows them to be more creative when approaching diverse problems ...

July 28, 2022
CI/CD for Data Lakes
Presented by Adi Polak
Managing your data like code Today, data lakes offer many advantages for cloud users. Everyone who needs storage such as object store, s3, azure blob, etc., can leverage data lakes. They ...

August 10, 2022
Build a robust data pipeline with Airflow, dbt, and Great Expectations—with Interactivity
Presented by Sam Bail
Hands-on data validation in a modern data stack Data quality has become a much discussed topic in the fields of data engineering and data science, and itâs become clear that data ...

May 3, 10, 17, 24, 31 & June 7, 2022
Essential Math for Data Science in 6 Weeks—with Interactivity
Presented by Thomas Nield
Achieve practical math proficiency using Python With the availability of data, there is a growing demand for talent who can analyze and make sense of it. This makes practical math all ...

July 13, 2022
Data Mesh in Practice—with Interactivity
Presented by Max Schultze, Arif Wider
How to set the foundations for federated data ownership The data lake paradigm is often considered the scalable successor of the more curated data warehouse approach when it comes to democratization ...


June 17, 2022
Designing Data Pipelines—with Interactivity
Presented by Vinoo Ganesh
The nuts and bolts of designing stable, extensible, and scalable data pipelines The data pipeline has become a fundamental component of the data science, data analyst, and data engineering workflow. Pipelines ...

Popular in interactive learning
See allCKA Prep: Aggregating RBAC Rules
By Benjamin Muschko
Verifies your ability to aggregate RBAC rules ...
Data Preprocessing: Normalizing and Scaling Data
By Sarah Guido
Learn how and when to normalize and scale your data ...
Cleaner Code for Data Science: Writing Unit Tests in R
By Charles Givre
Test, maintain, and debug your code with unit tests ...
Cleaner Code for Data Science: Writing Unit Tests in Python
By Charles Givre
Test, maintain, and debug your code with unit tests ...
Cleaner Code for Data Science: Logging in R
By Charles Givre
Use loggers to keep an eye on your code ...
Data Preprocessing: Feature Selection
By Sarah Guido
Select the best features for your machine learning model ...