June 2020
Beginner to intermediate
8h 7m
English
Closed Captioning available in English
Overview
In this 8 hr course, you'll learn to leverage PySpark for efficient big data analytics and machine learning. By mastering PySpark's libraries, you'll be equipped to process large-scale datasets and build scalable data pipelines.
What I will be able to do after this course
- Understand and apply PySpark components such as Spark SQL and MLlib.
- Develop scalable machine learning pipelines using PySpark.
- Perform exploratory data analysis on large datasets confidently.
- Learn effective strategies for data visualization in Jupyter with PySpark.
- Gain scalable solutions for big data challenges.
Course Instructor(s)
Danny Meijer is a seasoned expert in big data technologies and a passionate instructor. With years of hands-on experience in PySpark and a knack for making complex concepts accessible, Danny has empowered countless learners. His engaging style and emphasis on practical use cases offer a learning experience that is both enjoyable and effective.
Who is it for?
This course is ideal for data scientists who want to scale their analyses, data engineers aiming to refine big data workflows, and Python developers eager to dive into big data analytics. Learners should have a basic understanding of Python programming and some foundational knowledge of machine learning to benefit the most.
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