Machine Learning with Apache Spark using Scala

About this course

Do you want to master Machine Learning at scale using one of the most powerful Big Data frameworks in the world? This course will teach you Machine Learning with Apache Spark 3.0 and Scala, step by step, through real-world projects and hands-on coding examples.Apache Spark is the industry-standard framework for processing and analyzing large datasets. Its MLlib (Machine Learning Library) provides scalable implementations of machine learning algorithms, making it possible to train, evaluate, and deploy models on massive amounts of data efficiently. Combined with Scala, the native language of Spark, you’ll learn how to build and optimize end-to-end machine learning pipelines.This course is designed for beginners to intermediate learners who want to get practical experience in applying machine learning techniques in Spark. You’ll start with Big Data and Spark basics, then move on to core machine learning concepts, and finally apply them to real-world datasets through hands-on projects like rain prediction, ad click prediction, iris flower classification, and customer segmentation.By the end of this course, you will have the skills and confidence to build scalable machine learning models using Spark 3.0 and Scala—skills that are highly in-demand in industries such as finance, e-commerce, telecom, and technology.What You Will LearnIntroduction to Machine Learning & Spark MLlibBasics of machine learning, types (supervised, unsupervised, classification, regression, clustering).What is Spark ML? How Spark MLlib simplifies building ML models at scale.Apache Spark Basics (Option

Course objectives

• master machine learning concepts using Spark
• gain practical coding experience in Scala
• build and optimize machine learning workflows