Skills you'll learn:
scikit-learnData cleaning
Data Engineering
Course
Gain hands-on experience in data engineering by practicing the creation of ETL, NLP, and machine learning pipelines. This practical knowledge will prepare you for your project with our industry partner, Figure 8.
Gain hands-on experience in data engineering by practicing the creation of ETL, NLP, and machine learning pipelines. This practical knowledge will prepare you for your project with our industry partner, Figure 8.
Built in collaboration with
IBM
Advanced
1 month
Last Updated November 4, 2024
Prerequisites:
Basic SQLPython for data scienceJSONRelational database proficiency
Advanced
1 month
Last Updated November 4, 2024
Skills you'll learn:
scikit-learn • Data cleaning • Machine learning pipeline creation • Part of speech tagging
Prerequisites:
Basic SQL • Python for data science • JSON
Course Lessons
Lesson 1
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.
Lesson 2
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.
Lesson 3
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.
Lesson 4
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.
Lesson 5 • Project
Project: Disaster Response Pipeline
You’ll build a machine learning pipeline to categorize emergency messages based on the needs communicated by the sender.
Taught By The Best
Andrew Paster
Instructor
Andrew has an engineering degree from Yale, and has used his data science skills to build a jewelry business from the ground up. He has additionally created courses for Udacity's Self-Driving Car Engineer Nanodegree program.
Juno Lee
Curriculum Lead at Udacity
Juno is the curriculum lead for the School of Data Science. She has been sharing her passion for data and teaching, building several courses at Udacity. As a data scientist, she built recommendation engines, computer vision and NLP models, and tools to analyze user behavior.
Arpan Chakraborty
Instructor
Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.
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