学生对 EDUCBA 提供的 PySpark & Python: Hands-On Guide to Data Processing 的评价和反馈
课程概述
热门审阅
GL
Nov 1, 2025
The course’s focus on data cleaning, transformation, and performance optimization was considered both comprehensive and industry-relevant.
MN
Oct 26, 2025
Insightful but somewhat basic; lacks depth and advanced techniques for seasoned PySpark and Python professionals.
26 - PySpark & Python: Hands-On Guide to Data Processing 的 37 个评论(共 37 个)
创建者 ingemilton
•Oct 19, 2025
Covering core transformations, joins and scalable data pipelines. The hands‑on approach is welcome, though some sections feel a bit rushed and assume prior Python comfort. Good value for brushing up on big‑data basics with Spark.
创建者 latrice b
•Oct 10, 2025
Great course! I learned to handle massive datasets with ease. The hands-on approach made me confident in building end-to-end PySpark data pipelines.
创建者 Georgia L
•Nov 2, 2025
The course’s focus on data cleaning, transformation, and performance optimization was considered both comprehensive and industry-relevant.
创建者 Debashree S
•Oct 2, 2025
Hands-on guidance simplifies complex PySpark workflows, boosting confidence in professional data engineering tasks
创建者 annamarie h
•Sep 30, 2025
Valuable resource, explains PySpark functions clearly with effective Python integration for processing tasks.
创建者 Annie D
•Nov 9, 2025
Very professional delivery with high-quality explanations. PySpark now feels simple thanks to this course!
创建者 delilah b
•Oct 5, 2025
Fantastic course! Easy-to-follow lessons and solid hands-on exercises for mastering PySpark.
创建者 taryn b
•Oct 31, 2025
I finally understand how to optimize and process big datasets with PySpark.
创建者 Delma B
•Nov 3, 2025
Learned a lot about Spark optimization and Python integration efficiently.
创建者 elainaminer
•Dec 21, 2025
Using Python alongside Spark makes the learning experience more approachable, especially for those coming from a Python background.
创建者 Prakhar J
•Feb 24, 2026
didn't find the course that much informative, can be better
创建者 goran b
•Mar 5, 2026
bad explanations