PySpark & AWS: Master Big Data With PySpark and AWS

Mastering AWS & PySpark: Spark, PySpark, AWS, Spark Ecosystem, Hadoop, and Spark Applications [AWS, Hadoop, Pyspark]

4.45 (2573 reviews)

Udemy

platform

English

language

Data Science

What you will learn

● The introduction and importance of Big Data.

● Practical explanation and live coding with PySpark.

● Spark applications

● Spark EcoSystem

● Spark Architecture

● Hadoop EcoSystem

● Hadoop Architecture

● PySpark RDDs

● PySpark RDD transformations

● PySpark RDD actions

● PySpark DataFrames

● PySpark DataFrames transformations

● PySpark DataFrames actions

● Collaborative filtering in PySpark

● Spark Streaming

● ETL Pipeline

● CDC and Replication on Going

Course Gallery

PySpark & AWS: Master Big Data With PySpark and AWS – Screenshot 1 — Screenshot 1 – PySpark & AWS: Master Big Data With PySpark and AWS

PySpark & AWS: Master Big Data With PySpark and AWS – Screenshot 2 — Screenshot 2 – PySpark & AWS: Master Big Data With PySpark and AWS

PySpark & AWS: Master Big Data With PySpark and AWS – Screenshot 3 — Screenshot 3 – PySpark & AWS: Master Big Data With PySpark and AWS

PySpark & AWS: Master Big Data With PySpark and AWS – Screenshot 4 — Screenshot 4 – PySpark & AWS: Master Big Data With PySpark and AWS

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Comidoc Review

Our Verdict

The PySpark & AWS course is an ideal starting point for beginners wanting to explore big data processing. Though there are areas to improve, particularly in the AWS sections, it succeeds at providing hands-on experience with various essential tools and concepts within PySpark. To optimize your learning experience, consider supplementing this course with additional resources on AWS integration and refining Spark programming techniques. Remember, mastery of big data processing emerges from persistent practice and continuously expanding your knowledge base.

What We Liked

Comprehensive coverage of PySpark and AWS with practical projects to reinforce learning.
Detailed explanations for beginners, making it accessible for those new to the Spark ecosystem.
Dynamic problem-solving approach in addressing tech service updates and errors.

Potential Drawbacks

Lacks in-depth explanations of certain concepts, assuming prior foundational knowledge.
AWS sections can be confusing with outdated content and some critical steps missing.
Some modules like Collaborative Filtering and Spark Streaming seem rushed without proper context.