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What You Will Learn
Syllabus
Data Engineering
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Prerequisite Knowledge
To be successful in this program, you should have intermediate Python and SQL skills.See detailed requirements.
Data Modeling
Learn to create relational and NoSQL data models to fit the diverse needs of data consumers. Use ETL to build databases in PostgreSQL and Apache Cassandra.
Data Modeling with PostgresData Modeling with Apache CassandraCloud Data Warehouses
Sharpen your data warehousing skills and deepen your understanding of data infrastructure. Create cloud-based data warehouses on Amazon Web Services (AWS).
Build a Cloud Data WarehouseSpark and Data Lakes
Understand the big data ecosystem and how to use Spark to work with massive datasets. Store big data in a data lake and query it with Spark.
Build a Data LakeData Pipelines with Airflow
Schedule, automate, and monitor data pipelines using Apache Airflow. Run data quality checks, track data lineage, and work with data pipelines in production.
Data Pipelines with AirflowCapstone Project
Combine what you've learned throughout the program to build your own data engineering portfolio project.
Data Engineering Capstone
Real-world projects from industry experts
With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.
Technical mentor support
Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you and keeping you on track.
Personal career coach and career services
You’ll have access to career coaching sessions, interview prep advice, and resume and online professional profile reviews to help you grow in your career.
Flexible learning program
Get a custom learning plan tailored to fit your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
Program OfferingsFull list of offerings included:
Enrollment includes:
Class Content
Content Co-created with Insight
Real-world projects
Project reviews
Project feedback from experienced reviewers
Student Services
Technical mentor support
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Student community
Improved
Career services
Personal career coaching
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Interview preparations
Resume services
Github review
LinkedIn profile review
Succeed with Personalized Services
We provide services customized for your needs at every step of your learning journey to ensure your success!
Experienced Project Reviewers
Project Reviewers
Technical Mentor Support
Technical Mentor Support
Personal Career Coach
Career Coaching
Get personalized feedback on your projects
Reviews By the numbers
2000+ project reviewers
1.8M projects reviewed
4.85/5 reviewer ratings
3 hour 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
Learn with the best
Amanda Moran
Developer Advocate at DataStax
Amanda is a developer Advocate for DataStax after spending the last 6 years as a Software Engineer on 4 different distributed databases. Her passion is bridging the gap between customers and engineering. She has degrees from University of Washington and Santa Clara University.
Ben Goldberg
Staff Engineer at SpotHero
In his career as an engineer, Ben Goldberg has worked in fields ranging from Computer Vision to Natural Language Processing. At SpotHero, he founded and built out their Data Engineering team, using Airflow as one of the key technologies.
Sameh El-Ansary
CEO at Novelari & Assistant Professor at Nile University
Sameh is the CEO of Novelari, lecturer at Nile University, and the American University in Cairo (AUC) where he lectured on security, distributed systems, software engineering, blockchain and BigData Engineering.
Olli Iivonen
Data Engineer at Wolt
Olli works as a Data Engineer at Wolt. He has several years of experience on building and managing data pipelines on various data warehousing environments and has been a fan and active user of Apache Airflow since its first incarnations.
David Drummond
VP of Engineering at Insight
David is VP of Engineering at Insight where he enjoys breaking down difficult concepts and helping others learn data engineering. David has a PhD in Physics from UC Riverside.
Judit Lantos
Data Engineer at Split
Judit was formerly an instructor at Insight Data Science helping software engineers and academic coders transition to DE roles. Currently, she is a Data Engineer at Split where she works on the statistical engine of their full-stack experimentation platform.
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.
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Data Engineer Nanodegree Program
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You'll have access to the Nanodegree program classroom and materials, plus expert project reviews.
Average Time
On average, successful students take null months to complete this program.
Benefits include
- Real-world projects from industry experts
- Technical mentor support
- Personal career coach & career services
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Program Details
PROGRAM OVERVIEW - WHY SHOULD I TAKE THIS PROGRAM?
Why should I enroll?
The data engineering field is expected to continue growing rapidly over the next several years, and there’s huge demand for data engineers across industries.
Udacity has collaborated with industry professionals to offer a world-class learning experience so you can advance your data engineering career. You will get hands-on experience running data pipelines, building relational and noSQL data models, creating databases on the cloud, and more. Udacity provides high-quality support as you master in-demand skills that will qualify you for high-value jobs in the data engineering field and help you land a job you love.
By the end of the Nanodegree program, you will have an impressive portfolio of real-world projects and valuable hands-on experience.What jobs will this program prepare me for?
This program is designed to prepare people to become data engineers. This includes job titles such as analytics engineer, big data engineer, data platform engineer, and others. Data engineering skills are also helpful for adjacent roles, such as data analysts, data scientists, machine learning engineers, or software engineers.How do I know if this program is right for me?
This Nanodegree program offers an ideal path for experienced programmers to advance their data engineering career. If you enjoy solving important technical challenges and want to learn to work with massive datasets, this is a great way to get hands-on practice with a variety of data engineering principles and techniques.
The prerequisites for this program include proficiency in Python and SQL. You should be comfortable writing functions and loops, using classes, working with libraries in Python. You should be comfortable querying data using joins, aggregations, and subqueries in SQL.
Enrollment and Admission
Do I need to apply? What are the admission criteria?
There is no application. This Nanodegree program accepts everyone, regardless of experience and specific background.What are the prerequisites for enrollment?
The Data Engineer Nanodegree program is designed for students with intermediate Python and SQL skills.
In order to successfully complete the program, students should be comfortable with the following programing concepts:- Strings, numbers, and variables
- Statements, operators, and expressions
- Lists, tuples, and dictionaries
- Conditions, loops
- Procedures, objects, modules, and libraries
- Troubleshooting and debugging
- Research & documentation
- Problem-solving
- Algorithms and data structures
- Joins
- Aggregations
- Subqueries
- Table definition and manipulation (Create, Update, Insert, Alter)
If I do not meet the requirements to enroll, what should I do?
Udacity’s Programming for Data Science with Python Nanodegree program is great preparation for the Data Engineer Nanodegree program. You’ll learn to code with Python and SQL.
Tuition and Term of Program
How is this Nanodegree program structured?
The Data Engineer Nanodegree program is comprised of content and curriculum to support six (6) projects. We estimate that students can complete the program in five (5) months working 10 hours per week.
Each project will be reviewed by the Udacity reviewer network. 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 Nanodegree program?
Access to this Nanodegree program 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 Nanodegree 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.
SOFTWARE AND HARDWARE - WHAT DO I NEED FOR THIS PROGRAM?
What software and versions will I need in this program?
There are no software and version requirements to complete this Nanodegree program. All coursework and projects can be done via Student Workspaces in the Udacity online classroom.