Do I need to take the courses in a specific order?

Yes, the courses have been sequenced in the order in which you should take them.

Will I receive a transcript from Duke University for completing this course?

No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Building Cloud Computing Solutions at Scale Specialization

Building Cloud Computing Solutions at Scale Specialization

Launch Your Career in Cloud Computing. Master strategies and tools to become proficient in developing data science and machine learning solutions in the Cloud

Instructor: Noah Gift

Included with Coursera Plus

Learn more

4 course series

Get in-depth knowledge of a subject

4.4

(293 reviews)

Intermediate level

Recommended experience

6 months at 5 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

4 course series

Get in-depth knowledge of a subject

4.4

(293 reviews)

Intermediate level

Recommended experience

6 months at 5 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

What you'll learn

Build websites involving serverless technology and virtual machines, using the best practices of DevOps
Create Microservices using technologies like Flask and Kubernetes that are continuously deployed to a Cloud platform: AWS, Azure or GCP
Apply Machine Learning Engineering to build a Flask web application that serves out Machine Learning predictions

Overview

With more companies leveraging software that runs on the Cloud, there is a growing need to find and hire individuals with the skills needed to build solutions on a variety of Cloud platforms. Employers agree: Cloud talent is hard to find. This Specialization is designed to address the Cloud talent gap by providing training to anyone interested in developing the job-ready, pragmatic skills needed for careers that leverage Cloud-native technologies.

In the first course, you will learn how to build foundational Cloud computing infrastructure, including websites involving serverless technology and virtual machines, using the best practices of DevOps. The second course will teach you how to build effective Microservices using technologies like Flask and Kubernetes that are continuously deployed to a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP). The third course begins to put together all of the Cloud concepts introduced in the first two courses to tackle more complex data engineering solutions. And finally, in the fourth course you will apply Machine Learning Engineering to build a Flask web application that serves out Machine Learning predictions.

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English

46 practice exercises

Advance your subject-matter expertise

Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from Duke University

Specialization - 4 course series

Each course concludes with a real-world project where you have an opportunity to build a Cloud-native solution. For each Cloud solution that you develop, you will also create a demo video and GitHub repository of code that can be showcased in your digital portfolio for employers. By the end of this Specialization, you will be well-equipped to begin designing Cloud-native data engineering and machine learning solutions.

Cloud Computing Foundations

Course 135 hours4.5 (273 ratings)View course

What you'll learn

Welcome to the first course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to build foundational Cloud computing infrastructure, including websites involving serverless technology and virtual machines. You will also learn how to apply Agile software development techniques to projects which will be useful in building portfolio projects and global-scale Cloud infrastructures.

Skills you'll gain

Continuous Delivery, Infrastructure As A Service (IaaS), Cloud Computing, Infrastructure as Code (IaC), DevOps, Serverless Computing, CI/CD, Amazon Web Services, Software Development Methodologies, Software Development, Agile Software Development, GitHub, Cloud Infrastructure, Platform As A Service (PaaS), and Technical Communication

Cloud Virtualization, Containers and APIs

Course 231 hours4.4 (130 ratings)View course

What you'll learn

Welcome to the second course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn to design Cloud-native systems with the fundamental building blocks of Cloud computing. These building blocks include virtual machines and containers. You will also learn how to build effective Microservices using technologies like Flask and Kubernetes. Finally, you will analyze successful patterns in Operations including: Effective alerts, load testing and Kaizen.

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 build a containerized Flask application that is continuously deployed to a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP).

Skills you'll gain

Kubernetes, Performance Testing, DevOps, Serverless Computing, Containerization, Microservices, Flask (Web Framework), Continuous Delivery, Cloud Computing, Cloud-Native Computing, Cloud Platforms, System Monitoring, Application Deployment, and Virtual Machines

Cloud Data Engineering

Course 341 hours4.1 (87 ratings)View course

What you'll learn

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).

Skills you'll gain

Serverless Computing, Big Data, Extract, Transform, Load, Software Engineering, Amazon S3, Command-Line Interface, Distributed Computing, Data Governance, Google Cloud Platform, Data Pipelines, Python Programming, Cloud Computing, Rust (Programming Language), Cloud Technologies, Continuous Integration, and NumPy

Cloud Machine Learning Engineering and MLOps

Course 413 hours4.5 (87 ratings)View course

What you'll learn

Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone. Finally, you will dive into emerging topics in Machine Learning including MLOps, Edge Machine Learning and AI APIs.

Skills you'll gain

Artificial Intelligence and Machine Learning (AI/ML), Continuous Delivery, Application Programming Interface (API), MLOps (Machine Learning Operations), Automation, Flask (Web Framework), Applied Machine Learning, Cloud API, Natural Language Processing, Computer Vision, Cloud Applications, Microsoft Azure, and Google Cloud Platform