Big Data Tutorials

In PySpark, we can drop one or more columns from a DataFrame using the .drop("column_name") method for a single column or .drop(["column1", "column2", ...]) for multiple columns.

The complete guide to file storage on AWS with S3 & EFS.

Master the basics of extracting, transforming, and loading data with Apache Airflow.

Take the first steps to master in-database machine learning using Snowflake Snowpark.

Learn the most popular unified platform for big data analytics - Databricks. The tutorial covers the seven core concepts and features of Databricks and how they interconnect to solve real-world issues in the modern data world.

Learn what BigQuery is, how it works, its differences from traditional data warehouses, and how to use the BigQuery console to query public datasets provided by Google.

Learn about the lasso and ridge techniques of regression. Compare and analyse the methods in detail.

Learn about Hadoop ecosystem, the architectures and how to start with Cloudera.

An intuitive guide for discovering the two most popular SQL commands to aggregate rows of your dataset

Implement a small blockchain in R and learn more about what a blockchain looks like and some of the core concepts behind it!

Learn all about Python dictionary comprehension: how you can use it to create dictionaries, to replace (nested) for loops or lambda functions with map(), filter() and reduce(), ...!