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Data Science with Apache Spark

New – Build data science solutions with cutting edge capabilities and techniques in Spark in this self-paced course.

GK# 7713

Course Overview

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The real power and value proposition of Apache Spark is its speed and ability to execute data science tasks. In this course, you’ll get a hands-on technical resource that will enable you to become comfortable and confident working with Spark for data science. We won't just explore Spark’s data science libraries, we’ll dive deeper and expand on the topics. This course starts by taking you through Spark and the steps required to build machine learning applications. You will learn to collect, clean, and visualize data. You will also learn to apply statistical analysis and mining operations using Spark. By the end , you will be able to perform your data scientist role, effectively communicating your findings to the relevant stakeholders.

Schedule

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What You'll Learn

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  • Understand the Spark programming language and its ecosystem of packages in Data Science
  • Work with interactive visualization packages in Spark
  • Understand the Spark machine learning algorithm to build a simple pipeline
  • Explore cutting edge data science methods
  • Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams
  • Study advanced Spark concepts, solution design patterns, and integration architectures
  • Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining

Outline

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On-Demand Outline

Getting started with Data Science

Data Acquisition and Cleaning

Statistical Data Analysis Techniques

Machine Learning; Neural Networks

Visual and Audio Analysis

Text Analysis

Parallel Techniques for Data Analysis

Who Should Attend

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If you are a data science enthusiast and want to work on larger sets of data and with cutting edge techniques of data science and Spark, then this course is for you. Familiarity with Spark and basic understanding of statistics is expected for this course.

Course Delivery

This course is available in the following formats:

On-Demand

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