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Learner Reviews & Feedback for Machine Learning with Apache Spark by IBM

4.5
stars
114 ratings

About the Course

Explore the exciting world of machine learning with this IBM course. Start by learning ML fundamentals before unlocking the power of Apache Spark to build and deploy ML models for data engineering applications. Dive into supervised and unsupervised learning techniques and discover the revolutionary possibilities of Generative AI through instructional readings and videos. Gain hands-on experience with Spark structured streaming, develop an understanding of data engineering and ML pipelines, and become proficient in evaluating ML models using SparkML. In practical labs, you'll utilize SparkML for regression, classification, and clustering, enabling you to construct prediction and classification models. Connect to Spark clusters, analyze SparkSQL datasets, perform ETL activities, and create ML models using Spark ML and sci-kit learn. Finally, demonstrate your acquired skills through a final assignment. This intermediate course is suitable for aspiring and experienced data engineers, as well as working professionals in data analysis and machine learning. Prior knowledge in Big Data, Hadoop, Spark, Python, and ETL is highly recommended for this course....

Top reviews

BS

Dec 18, 2023

This course gives good overview about ML with Spark.

SK

May 18, 2025

After completing this course. I gained much more knowledge about Spark that apply in ML project. and other topics such as data engineering, ML lifecycle.

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26 - 26 of 26 Reviews for Machine Learning with Apache Spark

By Tom W

•

Sep 27, 2024

Pretty good. I know feel moderately confident in using the spark shell. I'd have liked some more details about precisely how the partitioning of work for ML functions worked. I was a bit annoyed that the final project was more or less identical to the final project, which was a bit tedious. In general the exercises were kind of tedious are formulaic, but by the end it started being a bit fun because you came to remember all the times. It was good that this gave you hands on experience with pyspark.