In the PySpark course, you'll learn to leverage the capabilities of PySpark for big data processing, data analysis, and machine learning. You'll explore advanced techniques for data manipulation, gain practical experience in using PySpark, and become proficient in performing complex data tasks.

Becoming skilled in PySpark is a significant step in mastering big data analytics and data engineering.

Who will benefit:
The PySpark course is designed to provide individuals with the expertise to work with Apache Spark using Python. This course equips you with the knowledge and skills to harness the power of PySpark for big data processing, analysis, and machine learning.
This course is ideal for:

• Data engineers, data scientists, and data analysts
• Professionals working with big data and Apache Spark
• Individuals seeking to master PySpark for data processing and machine learning

Why we highly recommend this course:
We highly recommend the PySpark course to individuals looking to master big data analytics, data engineering, and data science using PySpark, Python, and Apache Spark. Proficiency in PySpark is a valuable asset in today's data-driven job market.

• Big Data Expertise: Learn to work with PySpark, an essential tool for big data processing, making you proficient in data engineering.
• Real-World Applications: The skills you acquire are immediately applicable in data engineering, data science, and big data roles.
• Career Advancement: Proficiency in PySpark is in high demand and can lead to rewarding career opportunities in big data and data analysis.

Duration:
Online: 30
Project: 12-16 Weeks

Prerequisite:
Successful completion of the Azure Databricks course and a basic understanding of Python are recommended.

Tools and technologies you will work with:

• Azure Databricks
• Azure Storage Account
• Spark variant of Python