- Data Pipelines
- Extract, Transform, Load
- Classification Algorithms
- Applied Machine Learning
- Data Transformation
- Regression Analysis
- Machine Learning
- Apache Hadoop
- Apache Spark
- PySpark
- Data Processing
- Supervised Learning
Machine Learning with Apache Spark
Completed by Anshika Singh
October 11, 2024
15 hours (approximately)
Anshika Singh'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
