Learn Spark SQL, DataFrames, and Machine Learning. Build scalable data pipelines and master distributed computing.
Sub Category
- Other IT & Software
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Objectives
- Master PySpark fundamentals, including RDDs, DataFrames, and the Spark architecture to process massive datasets efficiently. (117 chars)
- Build and deploy scalable machine learning pipelines using MLlib to solve real-world big data predictive analytics problems. (122 chars)
- Perform advanced data transformations, SQL queries, and performance tuning to optimize large-scale distributed computing tasks. (123 chars)
- Connect to various data sources like HDFS, S3, and NoSQL databases to build robust end-to-end data engineering workflows. (119 chars)
Pre Requisites
- A basic understanding of Python programming (variables, loops, and functions) and a fundamental grasp of SQL concepts are recommended.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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