Duke University

Advanced Data Engineering

This course is part of Large Language Model Operations (LLMOps) Specialization

Taught in English

Noah Gift
Alfredo Deza

Instructors: Noah Gift

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

23 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Create and manage data pipelines and their lifecycle

  • Connect and work with message queues to manage data processing

  • Use vector, graph, and key/value databases for data storage at scale

Details to know

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Recently updated!

February 2024

Assessments

14 quizzes

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

23 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Large Language Model Operations (LLMOps) Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

This week you will learn about databases and queues. You will find out the purpose and components of RabbitMQ including its use of queues and integration with Celery. Through hands-on exercises, they will gain experience connecting Celery to RabbitMQ within a Flask application and implementing task patterns like fire and forget and result retrieval. The course also covers core MySQL skills like interacting via the command line interface, manipulating databases, and integrating with Python web apps. By the end, students will have a foundational understanding of RabbitMQ, Celery, and MySQL that allows them to start building modern, asynchronous applications backed by a database.

What's included

22 videos14 readings4 quizzes1 discussion prompt1 ungraded lab

What's included

17 videos13 readings4 quizzes

This week we explore vector and graph databases, powerful tools for managing and extracting insights from large, complex datasets. As data volumes continue to grow, scalability is crucial. We'll learn how vector and graph databases can efficiently store data while maintaining relationships, enabling more advanced analytics. Through real-world examples, you'll see how these databases unlock scalability for machine learning, fraud detection, social networks, and more.

What's included

14 videos11 readings3 quizzes1 ungraded lab

In this final week, you will work on advanced real-world data engineering projects, applying everything you've learned. You'll encounter complex data challenges and devise solutions using the latest tools and techniques. This is an opportunity to bring together data engineering concepts covered throughout the course and implement them holistically to deliver impactful outcomes.

What's included

13 videos9 readings3 quizzes2 ungraded labs

Instructors

Noah Gift
Duke University
40 Courses90,738 learners

Offered by

Duke University

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