This is an introductory course designed for absolute beginners. While prior knowledge of Python is advantageous, participation is not mandatory.

This course offers comprehensive insights into Data Processing with PySpark. This course is designed to empower learners with the knowledge and skills needed to get started with Data processing with PySpark.

This course caters to a diverse audience, embracing those new to the field as Freshers. Data Analysts and Data Scientists will enhance their skills in Big data Processing, while Data Engineers will gain insights into seamless Spark architecture and data processing with PySpark.

RDDs: Resilient Distributed Datasets are Spark’s core, schema-less data structure for distributed, fault-tolerant processing of unstructured data with low-level control.

DataFrames: Higher-level Spark structures with named columns, optimized for structured data, supporting SQL-like queries and automatic performance tuning.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.