Do you want to learn data management and machine learning with PySpark? This is the course where you will learn about Big Data Analytics with PySpark and learn crucial techniques to implement this knowledge. In this course, you will learn how to operate PySpark. Basically, this is the package of Python that helps in solving data on a large scale. After doing this course, you will start performing ML tasks smoothly.
What should you learn PySpark from us?
You should take our course because this will help you to learn many things about PySpark which are truly essential for today's world. Here are the few course highlights topics we will cover.
You will gain expertise in the concepts of vital data analytics
creating data visualizations with the help of Jupyter
managing and working with a large set of databases.
Learning how to create a fast and scalable machine learning application
Learning how to load data fastly
performing data analysis tasks effectively
learning data streams with spark streaming
Mastering in big data analytics
So, at the end of the course, you will have sound knowledge of Big data analytics with PySpark and will perform several machine learning work effectively even you have to face a large dataset. Also, you have tips and some crucial tips that experts use for doing machine learning tasks.
Total: 39 lectures
Python versus Spark
Preparing for the Course
Connecting Jupyter to Spark
Getting to Know Spark
The Power of Spark
The Power of Spark MLlib
Spark Data Operations
Loading Data from CSV Files
Fixing Issues in Our Data – Part One
Fixing Issues in Our Data – Part Two
Grouping, Joining, and Aggregating – Part One
Grouping, Joining, and Aggregating – Part Two
Machine Learning with Spark
Building a Recommendation System with Spark MLlib – Part One
Building a Recommendation System with Spark MLlib – Part Two
Building a Recommendation System with Spark MLlib – Part Three
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