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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
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.
Applied Learning Project
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.

Course Information

Estimated Time: Approximately 4 months to complete Suggested pace of 4 hours/week

Difficulty: Intermediate

Free

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Course Information

Estimated Time: Approximately 4 months to complete Suggested pace of 4 hours/week

Difficulty: Intermediate