Nanodegree Data Engineering

Advanced

Data Engineer Specialization

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.

Days
Hours
Minutes
Seconds

Available on

Data Engineering to drive your earnings

+$27K

Average salary increase of Springboard software engineering students who provided pre- and post-course salaries

September 2022

In this robotic engineering bootcamp you will:

Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets.
Advance one’s blockchain skillset to the second generation of blockchain services with smart contracts utilizing the Ethereum network.

Meet the growing demand for Data Engineering and master the job-ready skills that will take your career to new heights.

Get an edge with human support

Work with a mentor, career coach, and more. They have your back and will hold you accountable.

Verify skills mastery

Project review cycle creates a feedback loop with multiple opportunities for improvement—until the concept is mastered.

Verify skills mastery

Learning accelerates as skilled mentors identify areas of achievement and potential for growth.

What will you learn

At the end of the program, you’ll combine your new skills by completing a capstone project.

Prerequisites

Students should have intermediate SQL and Python programming skills.

Data Modeling
In this course, you’ll learn to create relational and NoSQL data models to fit the diverse needs of data consumers. You’ll understand the differences between different data models, and how to choose the appropriate data model for a given situation. You’ll also build fluency in PostgreSQL and Apache Cassandra. Course Project Data Modeling with Postgres: In this project, you’ll model user activity data for a music streaming app called Sparkify. You’ll create a relational database and ETL pipeline designed to optimize queries for understanding what songs users are listening to. In PostgreSQL you will also define Fact and Dimension tables and insert data into your new tables.
Cloud Data Warehouses

In this course, you’ll learn to create cloud-based data warehouses. You’ll sharpen your data warehousing skills,
deepen your understanding of data infrastructure, and be introduced to data engineering on the cloud using Amazon Web Services (AWS).

Course Project: Build a Cloud Data Warehouse

In this project, you are tasked with building an ELT pipeline that extracts their data from S3, stages them in Redshift, and transforms data into a set of dimensional tables for their analytics team to continue finding insights in what songs their users are listening to.

Spark and Data Lakes

In this course, you will learn more about the big data ecosystem and how to use Spark to work with massive datasets. You’ll also learn about how to store big data in a data lake and query it with Spark.

 

Course Project
Build a Data Lake: In this project, you’ll build an ETL pipeline for a data lake. The data
resides in S3, in a directory of JSON logs on user activity on the app,
as well as a directory with JSON metadata on the songs in the app.
You will load data from S3, process the data into analytics tables
using Spark, and load them back into S3. You’ll deploy this Spark
process on a cluster using AWS.

Automate Data Pipelines

In this course, you’ll learn to schedule, automate, and monitor data pipelines using Apache Airflow. You’ll
learn to run data quality checks, track data lineage, and work with data pipelines in production.

 

Course Project
Data Pipelines with Airflow:

In this project, you’ll continue your work on the music streaming company’s data infrastructure by creating and automating a set of data pipelines. You’ll configure and schedule data pipelines with
Airflow and monitor and debug production pipelines.

Capstone Project

Combine what you’ve learned throughout the program to build your own data engineering portfolio project.

 

Course Project
Data Engineering
Capstone:

The purpose of the data engineering capstone project is to give you a chance to combine what you’ve learned throughout the program. This project will be an important part of your portfolio that will help you achieve your data engineering-related career goals. In this project, you’ll define the scope of the project and the data you’ll be working with. We’ll provide guidelines, suggestions, tips, and resources to help you be successful, but your project will be
unique to you. You’ll gather data from several different data sources; transform, combine, and summarize it; and create a clean database for others to analyze.

What is a professional certificate?

Develop the skills necessary to complete the job

Whether you want to start a new career or change your current career, Coursera’s professional certificates help you prepare for the position. Learn at your own pace, at a time and place that is most comfortable for you. Enroll today and discover a new career with a 7-day free trial. You can pause your classes or end the subscription at any time.

Practical projects

Apply your skills to practical projects and develop a portfolio that demonstrates your job readiness to potential employers. You will need to finish the projects correctly to get your certificate.

Get a professional credential

When you complete all the courses in the program, you earn a certificate that you can share with your professional network, as well as access to professional support resources to help you start your new career. Many professional certificates have partners interested in hiring staff who recognize the professional certificate credential, and others can help you prepare for the certificate exam. You can see more information on the pages of the particular professional certificate where it applies.

Program Offer It includes
Real world projects Yes
STUDENT SERVICES
Mentor Tech Support Yes
Student community Yes
CAREER SERVICES
CV support Yes
Freelance Projects Yes
Real World Project
Develop an End-to-End project that will allow you to interact in a real work environment.
Certificate to share
Get a certificate upon completion

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Get started right away and learn at your own pace.

Level

Intermediate – advance
ESTIMATED TIME
5 months complete
8 – 10 hours / week

English

Subtitles:  All languages

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Data Engineer Specialization

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✓ Affordable programs and free trial for 7 days.
✓ Apply your skills in practical projects
✓ Learn at your own pace
✓ Videos and course readings
✓ Graded tests and assignments
✓ Many programs do not require a degree or experience
✓ Certificate that can be shared after completion

To share in LinkedIn

You can share your Certificates in the Certifications section of your LinkedIn profile, on your printed resume, or in other documents.

FAQ

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