This Pyspark with Python course introduces participants to the various features of Spark with Python. During the course, learners will gain a comprehensive understanding of installing the Pyspark environment, working with DataFrames to handle missing values and perform filter operations, using GroupBy and aggregate functions, and utilising Pyspark’s Machine Learning Library (Mlib). The course also covers learning Linear Regression in depth as well as its implementation in Databricks. By the end of the course, a solid foundation will have been established on Pyspark and its applications in data science.
Overview
Syllabus
Tutorial 1-Pyspark With Python-Pyspark Introduction and Installation.
Tutorial 2-Pyspark With Python-Pyspark DataFrames- Part 1.
Tutorial 3- Pyspark With Python-Pyspark DataFrames- Handling Missing Values.
Tutorial 4- Pyspark With Python-Pyspark DataFrames- Filter Operations.
Tutorial 5- Pyspark With Python-GroupBy And Aggregate Functions.
Tutorial 6- Pyspark With Python-Introduction To Pyspark Mlib.
Tutorial 26- Linear Regression Indepth Maths Intuition- Data Science.
Tutorial 7- Pyspark With Python|Introduction To Databricks.
Tutorial 8- Pyspark Multiple Linear Regression Implementation In Databricks.
Taught by
Krish Naik
