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Cloud Data Engineering
Welcome to the third course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to apply Data Engineering to real-world projects using the Cloud computing concepts introduced in the first two courses of this series. By the end of this course, you will be able to develop Data Engineering applications and use software development best practices to create data engineering applications. These will include continuous deployment, code quality tools, logging, instrumentation and monitoring. Finally, you will use Cloud-native technologies to tackle complex data engineering solutions.
This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a serverless data engineering pipeline in a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP).
Duration
4 Months
Institution
Duke University
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Duke University.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$322
Total Est. Investment
$322
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Cloud Data Engineering program at Duke University are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.