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Big-Data with PySpark, Spark Streaming, Spark ML and Kafka
Rating: 4.0 out of 5(49 ratings)
618 students

Big-Data with PySpark, Spark Streaming, Spark ML and Kafka

BigData with PySpark, Spark Streaming, Spark ML, Kafka, IoT, Architecture, 40+ RDDs & Dataframes Functions, ML
Created byImplied Concepts AI
Last updated 5/2023
English

What you'll learn

  • Complete Pyspark for Big Data Engineers and Architects
  • Spark ML - Learn how to design Spark ML models with pipelines
  • Spark Streaming- Learn all about spark streaming
  • Learn how to do Big Data ETL jobs with 40+ data transformation and actions
  • Learn to be Big Data Architect with Kafka, Spark Architecture for real time and batch processing

Course content

10 sections • 49 lectures • 3h 45m total length

  • PySpark Course Introduction and Outline2:51
  • Important Notice0:27

    Very Important Notice


    Don't be perturbed if you see a prompt from Udemy to rate this course very early on.

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    Regards

    Implied Concepts AI

  • Why Spark4:07
  • Spark Logical Architecture3:48

Requirements

  • Basics of Python

Description

In the 'Mastering PySpark with Cloud Computing' course, you will:

  1. Learn to navigate the rapidly evolving digital industry: As more businesses migrate to cloud services, understanding and deploying Big Data Frameworks on the cloud has become an essential skill set.

  2. Gain proficiency in PySpark and Cloud Computing: You will master PySpark, one of the most potent Big Data Frameworks, and learn cluster-based cloud computing on platforms such as Azure HDInsight, AWS EMR, and GCP DataProc.

  3. Expand your knowledge beyond basic PySpark: The course covers advanced topics including Spark Streaming, Spark Machine Learning, Kafka, IoT, and more.

  4. Understand Spark Architecture and RDD: You will learn about Spark Architecture, Dataframe, and Resilient Distributed Datasets (RDD) by exploring 40+ Spark Transformation and Action methods.

  5. Benefit from high-quality visual aids: Complex concepts will be simplified through visual aids. This includes a detailed analysis of Tumbling Window, Sliding Window, and Watermarking in Spark Structured Streaming.

  6. Get hands-on with Spark Streaming: The course provides eight distinct examples to solidify your understanding of Spark Streaming.

  7. Explore Big Data Ingestion and Pre-processing: You'll delve into the intricacies of Big Data Ingestion and Pre-processing, SQL in PySpark.

  8. Learn Spark Machine Learning with real-world examples: Gain practical knowledge with real-world examples of Regression, Clustering, Decision Trees, and Topic Modeling using Pipelines.

Join our 'Mastering PySpark with Cloud Computing' course today to close any gaps in your knowledge of data architecture and cloud computing, and move forward in becoming a Big Data expert.



Who this course is for:

  • Big-Data, Spark, Spark Stream, Kafka, Python, Clusters,Spark Machine Learning at scale

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