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.