Apache Spark with Scala: Master Data Building & Analysis
Skills:
ML Pipelines85%
This course provides a complete journey into Apache Spark with Scala, designed for learners who want to analyze, design, implement, and evaluate big data applications. Beginning with the foundations of Spark architecture and Scala programming, learners will explore variables, functions, collections, and advanced Scala concepts such as traits, abstract classes, and exception handling. The course then advances into Spark RDD operations, streaming, windowing, and checkpointing, helping learners apply distributed transformations and implement real-time data pipelines. Finally, learners will construct integrated projects using Maven, connect Spark to external systems like Twitter APIs, and evaluate the impact of Hadoop 1.x vs 2.x in managing resources for scalable applications.
By the end of this course, participants will be able to apply Scala fundamentals, differentiate RDD transformations and actions, implement Spark Streaming with fault tolerance, and construct end-to-end real-time big data solutions—positioning themselves for roles in data engineering, big data analytics, and real-time application development.
Watch on Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: ML Pipelines
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
SQL Joins for Placement Interviews: The Complete Guide Every BTech Student Needs
Medium · Programming
SQL DML Explained — INSERT, UPDATE, and DELETE with Real Examples
Medium · Programming
Simple Linear Regression : What! Can your Second term Grades can predict your Final term Grades?
Medium · Data Science
Aggregate Functions in SQL for Data Science Interviews
Medium · Data Science
🎓
Tutor Explanation
DeepCamp AI