The course Data Engineering for Data Scientists on Udacity covers various topics including ETL pipelines, natural language processing, and machine learning pipelines. Students will learn how to access and combine data from different sources such as CSV, JSON, logs, APIs, and databases. They will also gain knowledge on preparing text data for analysis by performing tasks like tokenization, lemmatization, and removing stop words. The course will teach students how to transform and vectorize text data using scikit-learn, and build features using bag of words and tf-idf. Additionally, students will understand the advantages of using machine learning pipelines to streamline the data preparation and modeling process, and learn how to use feature unions to perform steps in parallel and create more complex workflows. The course includes a project where students will build a data pipeline to prepare message data from major natural disasters and create a machine learning pipeline to categorize emergency text messages based on the communicated need.