From 0 to 1: Spark for Data Science with Python

Data science and machine learning: two of the most profound technologies, are within your easy grasp! Simpliv’s course brings your data to life using Spark for analytics, machine learning and data science. Learn to implement complex algorithms like PageRank or Music Recommendations and much more.

From 0 to 1: Spark for Data Science with Python

Course Description

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. Get your data to fly using Spark for analytics, machine learning and data science. What Is Spark?: If you are an analyst or a data scientist, you're used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code. Analytics: Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ... Read More »

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. Get your data to fly using Spark for analytics, machine learning and data science.

What Is Spark?: If you are an analyst or a data scientist, you’re used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.

Analytics: Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease.

Machine Learning and Data Science: Spark’s core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We’ll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets.

What’s Covered?

In this Simpliv course, the following is covered:

  • Music Recommendations using Alternating Least Squares and the Audioscrobbler dataset
  • Dataframes and Spark SQL to work with Twitter data
  • Using the PageRank algorithm with Google web graph dataset
  • Using Spark Streaming for stream processing
  • Working with graph data using the Marvel Social network dataset
  • Resilient Distributed Datasets, Transformations (map, filter, flatMap), Actions (reduce, aggregate)
  • Pair RDDs , reduceByKey, combineByKey
  • Broadcast and Accumulator variables
  • Spark for MapReduce
  • The Java API for Spark
  • Spark SQL, Spark Streaming, MLlib and GraphFrames (GraphX for Python)
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Course Outcomes:
  • Use Spark for a variety of analytics and Machine Learning tasks
  • Implement complex algorithms like PageRank or Music Recommendations
  • Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
  • Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX
Course Details:

Target Audience

  • Analysts who want to leverage Spark for analyzing interesting datasets
  • Data Scientists who want a single engine for analyzing and modelling data as well as productionizing it
  • Engineers who want to use a distributed computing engine for batch or stream processing or both

Access Timeframe

Lifetime

Prerequisites

  • The course assumes knowledge of Python. You can write Python code directly in the PySpark shell. If you already have IPython Notebook installed, we'll show you how to configure it for Spark.
  • For the Java section, we assume basic knowledge of Java. An IDE which supports Maven, like IntelliJ IDEA/Eclipse would be helpful.
  • All examples work with or without Hadoop. If you would like to use Spark with Hadoop, you'll need to have Hadoop installed (either in pseudo-distributed or cluster mode).
Certificate Info:

Type of Certification

Certificate of Completion

Format of Certification

Digital

Professional Association/Affiliation

Certificates are recognized by the Association of Simpliv

Method of Obtaining Certification

Upon successful completion of a course, the learner can download their certificate from their Learner Dashboard.

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