- Applied Machine Learning
- Data Pipelines
- Feature Engineering
- Supervised Learning
- Extract, Transform, Load
- Data Processing
- Generative AI
- Apache Hadoop
- Unsupervised Learning
- PySpark
- Data Transformation
- Apache Spark
Machine Learning with Apache Spark
Completed by Sanika Patange
October 23, 2023
15 hours (approximately)
Sanika Patange'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
