Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
9 Hour(s) 1 Minute(s)
Language
English
Taught by
Loony Corn
Rating
4 views
Course Overview
Use Scala and Spark for data analysis, machine learning and analytics
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 and Scala for analytics, machine learning and data science
Let’s parse that.
What's 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.
Scala: Scala is a general purpose programming language - like Java or C++. It's functional programming nature and the availability of a REPL environment make it particularly suited for a distributed computing framework like Spark.
Analytics: Using Spark and Scala 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:
Scala Programming Constructs: Classes, Traits, First Class Functions, Closures, Currying, Case Classes
Lot's of cool stuff ..
- 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
.. and of course all the Spark basic and advanced features:
- 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 GraphX
Course Content
- 12 section(s)
- 55 lecture(s)
- Section 1 You, This Course and Us
- Section 2 Introduction to Spark
- Section 3 Resilient Distributed Datasets
- Section 4 Advanced RDDs: Pair Resilient Distributed Datasets
- Section 5 Advanced Spark: Accumulators, Spark Submit, MapReduce , Behind The Scenes
- Section 6 PageRank: Ranking Search Results
- Section 7 Spark SQL
- Section 8 MLlib in Spark: Build a recommendations engine
- Section 9 Spark Streaming
- Section 10 Graph Libraries
- Section 11 Scala Language Primer
- Section 12 Supplementary Installs
What You’ll Learn
- Use Spark for a variety of analytics and Machine Learning tasks , Understand functional programming constructs in Scala, 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, Write code in Scala REPL environments and build Scala applications with an IDE
Skills covered in this course
Reviews
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XXiao Lu
This is not a get-your-hands dirty course. Instructors were simply taking to code screenshots. You don't see them write or compile or run a single line of code. The syntax and API are also outdated. I have to look at official documentation to get the up-to-date API
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PPrasad Nadig
Well explained, well paced and to the point presentation of salient aspects of using Scala on Spark for data munging. I felt time spent watching the content was worth it.
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JJeffrey A. Brown
Excellent course but dated. Would be great if they update it for current version of Spark!
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WWilliam Schmidt
Yes, even though I've already taken other Scala and Spark courses, the authors offered an alternative approach to explaining some concepts (especially in the Scala primer section) which were very helpful.
