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Estimated Time
28 hours
Enroll by
September 22, 2021
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Prerequisites
Python, SQL, Statistics, Machine Learning
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What You Will Learn
Syllabus
Data Engineering
Prerequisite Knowledge
Python, SQL, Statistics, Machine Learning.
ETL Pipelines
Understand what ETL pipelines are and cccess and combine data from CSV, JSON, logs, APIs and databases.
Natural Language Processing
Prepare text data for analysis with tokenization, lemmatization, and removing stop words. Use scikit-learn to transform and vectorize text data and build features with bag of words and tf-idf.
Machine Learning Pipelines
Understand the advantages of using machine learning pipelines to streamline the data preparation and modeling process. Use feature unions to perform steps in parallel and create more complex workflows and complete a case study to build a full machine learning pipeline that prepares data and creates a model for a dataset.
Course Project: Build Disaster Response Pipelines
In this project, you’ll build a data pipeline to prepare the message data from major natural disasters around the world. You’ll build a machine learning pipeline to categorize emergency text messages based on the need communicated by the sender.
Data Scientist roles are growing by 45% year over year!
Introducing new Udacity Single Courses
Introducing new Udacity Single Courses
Our students asked and we listened. You can now get the in-demand tech skills you need faster and for less money by enrolling in one of our new, one-month Single Courses. You’ll get the specific job-ready skills you need in as little as four weeks and for a fraction of the cost.
Of course if you are looking for a more robust, in-depth education, you can still enroll in one of our 3-6 month Nanodegree programs.
Both programs are part-time and online, and they both offer 24/7 support, quality Udacity-produced content, courses created with the help of top tech companies, and more. You can always start with a Single Course and upgrade to a full Nanodegree program if you like.
Of course if you are looking for a more robust, in-depth education, you can still enroll in one of our 3-6 month Nanodegree programs.
Both programs are part-time and online, and they both offer 24/7 support, quality Udacity-produced content, courses created with the help of top tech companies, and more. You can always start with a Single Course and upgrade to a full Nanodegree program if you like.
Course OfferingsFull list of offerings included:
Enrollment Includes:
Class Content
Real-world projects
Project reviews
Project feedback from experienced reviewers
Student Services
Technical mentor support
New
Student community
Improved
Succeed with Personalized Services
We provide services customized for your needs at every step of your learning journey to ensure your success!
Get timely feedback on your projects
Reviews By the numbers
1,400+ project reviewers
2.7M projects reviewed
88/100 reviewer rating
1.1 hours avg project review turnaround time
Reviewer Services
- Personalized feedback
- Unlimited submissions and feedback loops
- Practical tips and industry best practices
- Additional suggested resources to improve
Mentors available to answer your questions
Mentors by the numbers
1,400+ technical mentors
0.85 hours median response time
Mentorship Services
- Support for all your technical questions
- Questions answered quickly by our team of technical mentors
Learn with the best
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.
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.
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.
Data Engineering
Get Started Today
- Enroll Now
Learn
How to pull data, store it, and build ETL, NLP and machine-learning data pipelines with Python.
Average Time
On average, successful students take 28 hours to complete this program.
Benefits include
- Real-world projects from industry experts
- Technical mentor support
Program Details
Do I need to apply? What are the admission criteria?
No. This Course accepts all applicants regardless of experience and specific background.What are the prerequisites for enrollment?
Machine Learning:- Supervised and Unsupervised methods equivalent to those taught in the Intro to Machine Learning Nanodegree Program.
- Experience with Python Programming including writing functions, building basic applications, and common libraries like NumPy and pandas
- SQL programming including querying databases, using joins, aggregations, and subqueries
- Comfortable using the Terminal and Github
- Descriptive Statistics including calculating measures of center and spread
- Inferential Statistics including sampling distributions, hypothesis testing
How is this course structured?
The Data Engineering course is comprised of content and curriculum to support one project. We estimate that students can complete the program in 28 hours.
The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.How long is this course?
Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.Can I switch my start date? Can I get a refund?
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.What software and versions will I need in this course?
You’ll need access to the Internet, and a 64 bit computer. Additional software: need to be able to download and run Python 3.7.