Enterprise Scala and Spark

Enterprise Data Science is a wide-ranging field built on many core technologies and paradigms that combine to provide a robust solution. Some of these technologies and/or practices include ETL, Data Engineering, Machine Learning, Network/Grid/Cloud engineering, and Business Rules.

This course explores some of these areas and provides experienced developers with a ‘big-picture’ understanding of how these technologies fit together for a professional-grade enterprise Data Science environment. You’ll learn Scala and Functional programming as well as Spark and Enterprise Integration techniques in a "breadth"-based approach for maximum exposure into the world of Enterprise Data Science. The course has several hands-on labs integrated throughout the training, but additional "depth"-based learning should be expected after this class to master Enterprise Data Science.

    Dec 7 2020

    December 7 - 11, 2020 | 10:00 AM - 6:00 PM (EST) | Virtual Classroom Live

    Date: 12/07/2020 - 12/11/2020 (Monday - Friday) | 10:00 AM - 6:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    Enterprise Scala and Spark

    December 7 - 11, 2020 | 10:00 AM - 6:00 PM (EST) | Virtual Classroom Live


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Functional Programming in Scala

  • Functional Programming
  • Scala Overview
  • Scala vs. Python vs. Java vs. R
  • REPL in Scala
  • Installing Scala
  • Hello, Scala

Introduction to Scala

  • Classes and Objects
  • Traits
  • Mixins
  • High-Order Functions
  • Types and Inference
  • Lists
  • Annotations
  • Collections
  • Pattern Matching
    Using Java in Scala
  • Futures, Promises, and Parallel Collections (Concurrency)
  • Functional Programming Overview

Spark Core

  • Hadoop and Spark Overview
  • File I/O with HDFS
  • Data Frames and Resilient Distributed Datasets
  • Spark SQL
  • In-memory lookups
  • Essential AI with MLLib
  • Using Web Notebooks (Optional)

Working with NoSQL

  • Not Only SQL
  • Relational Data
  • Sqoop
  • Columnar Databases
  • Cassandra
  • Document Databases
  • Key/Value Databases
  • Graph Databases
  • Neo4J
  • GraphX
  • Hive in Spark

Spark Streaming

  • Spark Streaming Model
  • Streaming with Kafka

ML Lib

  • Machine Learning Essentials
  • Spark ML/MLLib
  • MLLib and Streaming
  • MLlib, Streaming, and Kafka

Enterprise Integration

  • Enterprise Service and Message Busses
  • Lambda Architecture

Join an engaging hands-on learning environment, where you’ll learn:

  • Essential Scala programming, leveraging your existing OO development experience
  • How to write essential Spark programs and perform exploratory data analysis in Scala and the Spark shell
  • Work with Spark Core
  • Work with NoSQL
  • How to write programs for Spark Streaming in Scala

This course has a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work.

This “skills-centric” course is about 50% hands-on lab and 50% lecture, designed to train attendees in core Spark and Scala skills, coupling the most current, effective techniques with the soundest industry practices. Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review.

Before attending this course, you should have:

  • Experience in Java development, object-oriented enterprise applications at a basic level
  • Familiarity with Eclipse
  • Be comfortable with the Linux/Unix command line, including editing text files

 

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