Udemy - Pyspark For Data Scientists

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Udemy - Pyspark For Data Scientists (Size: 2.2 GB)
  1 - BIG DATA HISTORY PART 1.mp4 332.8 MB
  10 - Spark RDD Transformation Part 3.mp4 285.6 MB
  11 - RDD Action.mp4 117 MB
  12 - DataFrame Part 1.mp4 231 MB
  13 - DataFrame Part 2.mp4 96.4 MB
  14 - Sparkshell sparksubmit running spark in local.mp4 172.2 MB
  2 - BIG DATA HISTORY PART 2.mp4 93.1 MB
  3 - RDD Introduction.mp4 99.8 MB
  4 - Spark Ecosystem.mp4 111.3 MB
  5 - Spark Lazy Evulation.mp4 13.9 MB
  6 - Spark RDD Setup On Google Colab.mp4 99.9 MB
  7 - Spark context Spark Session.mp4 96.5 MB
  8 - Spark RDD Transformation Part 1.mp4 253.3 MB
  9 - Spark RDD Transformation Part 2.mp4 279.5 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 16 total files

Description


Pyspark For Data Scientists

https://FreeCourseWeb.com

Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.23 GB | Duration: 4h 43m

PySpark for Data Scientists

What you'll learn
Foundations of PySpark: Gain a solid understanding of fundamental PySpark concepts and principles.
Data Manipulation Techniques: Explore key data manipulation techniques such as dataframes, RDDs, and SQL queries in PySpark.
Distributed Data Processing: Learn techniques for distributed data processing and optimisation.
Data Preparation: Understand and implement strategies for data cleaning and transformation.

Requirements
Basic Understanding of Python Programming: This includes familiarity with libraries such as NumPy and Pandas.
Knowledge of Data Science Fundamentals: Understanding of data manipulation, exploratory data analysis, and basic machine learning concepts.
Familiarity with Big Data Concepts: Basic knowledge of big data concepts and distributed computing is beneficial but not required.

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