PySpark and AWS: Master Big Data with PySpark and AWS - Introduction to Course

This course covers data analysis from basic to advanced levels using PySpark. It explores Spark RDF data frames, Spark SQL queries, transformations, and actions. The course delves into the Spark and Hadoop ecosystem, using Databricks for running scripts. It also includes leveraging AWS cloud services for data engineering. The methodology involves lectures, quizzes, and projects, culminating in a final project on CDC pipeline using PySpark, Hadoop, and AWS.

What is the primary tool used for data analysis in this course?

• Hadoop

• PySpark

• Python

• SQL

Which environment is used for running Spark scripts in this course?

• Google Cloud

• Databricks

• Azure

• AWS

What cloud service is emphasized for data engineers in this course?

• Google Cloud

• Azure

• AWS

• IBM Cloud

What is the final project of the course focused on?

• Developing a machine learning model

• Creating a CDC pipeline

• Building a data warehouse

• Designing a web application

What methodology does the course follow for teaching?

• Lectures and quizzes with discussions

• Self-study and projects

• Lectures and exams

• Group discussions and presentations