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

Big-Data with PySpark, Spark Streaming, Spark ML and Kafka, available at $19.99, has an average rating of 4.1, with 49 lectures, based on 47 reviews, and has 610 subscribers.

You will learn about 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 This course is ideal for individuals who are Big-Data, Spark, Spark Stream, Kafka, Python, Clusters,Spark Machine Learning at scale It is particularly useful for Big-Data, Spark, Spark Stream, Kafka, Python, Clusters,Spark Machine Learning at scale.

Enroll now: Big-Data with PySpark, Spark Streaming, Spark ML and Kafka

Summary

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

Price: $19.99

Average Rating: 4.1

Number of Lectures: 49

Number of Published Lectures: 49

Number of Curriculum Items: 49

Number of Published Curriculum Objects: 49

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

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

Target Audiences

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

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

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.
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.
Expand your knowledge beyond basic PySpark: The course covers advanced topics including Spark Streaming, Spark Machine Learning, Kafka, IoT, and more.
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.
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.
Get hands-on with Spark Streaming: The course provides eight distinct examples to solidify your understanding of Spark Streaming.
Explore Big Data Ingestion and Pre-processing: You’ll delve into the intricacies of Big Data Ingestion and Pre-processing, SQL in PySpark.
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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: PySpark Course Introduction and Outline

Lecture 2: Important Notice

Lecture 3: Why Spark

Lecture 4: Spark Logical Architecture

Chapter 2: PySpark Installation

Lecture 1: Spark Installation Intro and Outline

Lecture 2: Anaconda Installation

Lecture 3: Java Run Time Installation

Lecture 4: Spark-Hadoop Libraries

Lecture 5: Environment Variables

Lecture 6: Final Setup and Permissions

Chapter 3: Cloud based Libraries Setup – Azure, AWS, GCP

Lecture 1: Cloud File Systems Installation – Azure,AWS,GCP – 1

Lecture 2: Cloud File Systems Installation – Azure,AWS,GCP – 2

Chapter 4: PySpark Hands On – First Job

Lecture 1: First Spark Job

Lecture 2: Spark Job with Could Systems

Chapter 5: Spark Core

Lecture 1: Spark Context Vs Spark Sessions

Lecture 2: Spark Data-Frames

Chapter 6: PySpark – Transformation and Actions

Lecture 1: RDD Transformations and Actions – 1

Lecture 2: RDD Transformations and Actions – 2

Lecture 3: DataFrames – Transformations and Actions -1

Lecture 4: DataFrames – Transformations and Actions – 2

Chapter 7: PySpark Clusters on Cloud – Azure, AWS, GCP

Lecture 1: Azure HDInsights Intro

Lecture 2: Azure HDInsights – 2

Lecture 3: Cloud Cluster Demo – 1

Lecture 4: Cloud Cluster Demo – 2 – RDD Operations

Lecture 5: Cloud Cluster Demo – 3 – DataFrames Operations

Lecture 6: GCP DataProc Clusters

Lecture 7: AWS EMR Cluster

Chapter 8: BigData Examples

Lecture 1: BigData Ingestion and Preprocessing

Lecture 2: PySpark – SQL

Chapter 9: Spark Streaming with Kafka IoT Pipeline

Lecture 1: Spark Streaming Introduction

Lecture 2: Popular Big Data Streaming Processing Frameworks

Lecture 3: Spark Streaming Vs Spark Structured Streaming

Lecture 4: Spark Streaming Hands-on Demo Introduction

Lecture 5: Spark Streaming Hands-on – Socket Streaming

Lecture 6: Spark Streaming Hands-on – File Streaming

Lecture 7: Kafka, Zookeeper, Pyspark Startup Scripts

Lecture 8: Kafka – PySpark Ex-1

Lecture 9: Kafka – PySpark Ex-2

Lecture 10: Kafka – PySpark Ex-3

Lecture 11: Kafka – PySpark Ex-4

Lecture 12: Kafka – PySpark Ex-5

Lecture 13: Spark Streaming – Tumbling and Sliding Window

Lecture 14: Kafka – PySpark Ex- 6 & 7

Lecture 15: Spark Stream – WaterMarking & Ex – 8

Chapter 10: Spark Machine Learning

Lecture 1: Why SparkML, What are Advantages of Spark Machine Learning

Lecture 2: SparkML – Linear Regression Demo

Lecture 3: SparkML Logistic Regression Demo

Lecture 4: SparkML Decision Trees Demo

Lecture 5: SparkML_Clustering Demo

Instructors

Implied Concepts AI
Academy and Consultancy

Rating Distribution

1 stars: 0 votes
2 stars: 5 votes
3 stars: 10 votes
4 stars: 16 votes
5 stars: 16 votes

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