Data Engineering

In data engineering for data scientists, you will practice building ETL, NLP, and machine learning pipelines. This will prepare you for the project with our industry partner Figure 8.

• Introduction to Data Engineering
• You will get an introduction to the data engineering for data scientists course and project. The lessons include ETL pipelines, natural language pipelines, and machine learning pipelines.
• ETL Pipelines
• ETL stands for extract, transform, and load. This is the most common type of data pipeline, and you will practice each step in this lesson.
• NLP Pipelines
• In order to complete the project at the end of the course, you will need some natural language processing skills. Here you will practice engineering machine learning features from text data.
• Machine Learning Pipelines
• You'll use the Scikit-Learn package to code a machine learning pipeline. With these skills, you can ingest data, create features, and train a machine learning algorithm in just one step.
• Project: Disaster Response Pipeline
• You’ll build a machine learning pipeline to categorize emergency messages based on the needs communicated by the sender.