Master big data analytics with PySpark through 20+ hands-on examples, leveraging Spark 3 and cloud computing for efficient data processing.
Dive into the exciting world of big data with this PySpark course! You’ll get hands-on experience analyzing large data sets using Python, while learning from an industry expert. By the end, you'll confidently run analyses in the cloud. Fun guaranteed!
PySpark tutorial with 20+ hands-on examples of analyzing large data sets on your desktop or on Hadoop with Python!
New! Updated for Spark 3, more hands-on exercises, and a stronger focus on DataFrames and Structured Streaming.
“Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark and specifically PySpark. Employers including Amazon, EBay, NASA JPL, and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think.
Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples, and then scale them up to run on cloud computing services in this course. You'll be learning from an ex-engineer and senior manager from Amazon and IMDb.
Learn the concepts of Spark's DataFrames and Resilient Distributed Datastores
Develop and run Spark jobs quickly using Python and pyspark
Translate complex analysis problems into iterative or multi-stage Spark scripts
Scale up to larger data sets using Amazon's Elastic MapReduce service
Understand how Hadoop YARN distributes Spark across computing clusters
Learn about other Spark technologies, like Spark SQL, Spark Streaming, and GraphX
By the end of this course, you'll be running code that analyzes gigabytes worth of information – in the cloud – in a matter of minutes.Â
This course uses the familiar Python programming language; if you'd rather use Scala to get the best performance out of Spark, see my "Apache Spark with Scala - Hands On with Big Data" course instead.
We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most “popular" superhero is – and develop a system to find “degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You'll find the answer.
This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together – both on your own system, and in the cloud using Amazon's Elastic MapReduce service. 7 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX.
Wrangling big data with Apache Spark is an important skill in today's technical world. Enroll now!
" I studied "Taming Big Data with Apache Spark and Python" with Frank Kane, and helped me build a great platform for Big Data as a Service for my company. I recommend the course! " - Cleuton Sampaio De Melo Jr.
Use DataFrames and Structured Streaming in Spark 3
Use the MLLib machine learning library to answer common data mining questions
Understand how Spark Streaming lets your process continuous streams of data in real time
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Sundog Education's mission is to make highly valuable career skills in data engineering, data science, generative AI, AWS, and machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you, at prices anyone can afford. Sundog Education is led by Frank Kane and owned by Frank's company, Sundog Software...
Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. As an Amazon “bar raiser,” he held veto authority over hiring decisions across the company, interviewed over 1,000 candidates, and hired and managed hundreds. He holds 17 issued patents in the...
Our mission is to make highly valuable skills in machine learning, big data, AI, and data science accessible at prices anyone in the world can afford. Our current online courses have reached over 500,000 students worldwide. Sundog Education CEO, Frank Kane, spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations...
the course is great specially the hands on but it seems that we must have big project that grab attention in our cv's but totally the course is perfect
really good and very clear
Awesome course on running big data jobs on Apache Spark using Python. As usual, Frank explains things very clearly and points out various items to watch out for and make sure you have set up correctly. There are many ways that a Spark job can fail or have issues, such as running out of memory, and Frank does a great job of pointing many of those out.
Frank Kane delivers again. The material was clear and well-presented.
Good instructor and good content.
the course is good, for beginners. It's good, but I suggest checking concepts in articles and at the same time watching the video will help to make strong concepts in mind.
I really liked it, this isnt the first time i purchase a course from this professor and the material was clearly well explained. I would have liked more advance excercises to practice but i also have them at home so its not a big deal
Cool presentation, like always :)
The setup instructions for the environment were good. I didn't have to iterate through the steps. the recording was very accurate.
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Akash S.
Nice