From 0 to 1 : Spark for Data Science with Python

About this course

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  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. 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: Lot's of cool stuff .. Music Recommendations using Alternating Least Squares and the Audioscrobbler datasetDataframes and Spark SQL to work with Twitter dataUsing the PageRank algorithm with Google web graph datasetUsing 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 , red