- Applied Machine Learning
- Supervised Learning
- Predictive Modeling
- Unsupervised Learning
- PySpark
- Data Transformation
- Machine Learning
- Data Processing
- Data Pipelines
- Apache Spark
- Generative AI
- Extract, Transform, Load
Machine Learning with Apache Spark
Completed by Cyrille Praz
April 11, 2024
15 hours (approximately)
Cyrille Praz'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
