- Apache Hadoop
- Generative AI
- Data Pipelines
- Supervised Learning
- Data Processing
- Regression Analysis
- PySpark
- Classification And Regression Tree (CART)
- Machine Learning
- Extract, Transform, Load
- Unsupervised Learning
- Predictive Modeling
Machine Learning with Apache Spark
Completed by Aditya Nair Balasubramanian
June 8, 2025
15 hours (approximately)
Aditya Nair Balasubramanian's account is verified. Coursera certifies their successful completion of Machine Learning with Apache Spark
What you will learn
Describe ML, explain its role in data engineering, summarize generative AI, discuss Spark's uses, and analyze ML pipelines and model persistence.
Evaluate ML models, distinguish between regression, classification, and clustering models, and compare data engineering pipelines with ML pipelines.
Construct the data analysis processes using Spark SQL, and perform regression, classification, and clustering using SparkML.
Demonstrate connecting to Spark clusters, build ML pipelines, perform feature extraction and transformation, and model persistence.
Skills you will gain
