Discover the Specialization in Building Cloud Computing Solutions at Scale, designed to bridge the Cloud talent gap and equip individuals with the skills needed for Cloud-native technology careers.
Throughout the four courses, you will master building foundational Cloud computing infrastructure, creating effective Microservices, applying Data Engineering to real-world projects, and implementing Machine Learning Engineering applications. The Specialization is ideal for beginners and intermediate students interested in Cloud computing, data science, machine learning, and data engineering.
Upon completion, you will be equipped with the skills to develop job-ready solutions on a variety of Cloud platforms, enhancing your career prospects in the Cloud computing industry.
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Gain practical skills in Cloud computing infrastructure, Microservices, Data Engineering, and Machine Learning Engineering, using Cloud platforms such as AWS, Azure, or GCP.
Welcome to the first course in the Specialization, where you will learn to build foundational Cloud computing infrastructure, including websites with serverless technology and virtual machines. Apply Agile software development techniques to projects, and build a statically hosted website using the Hugo framework, AWS Code Pipelines, AWS S3, and GitHub.
In this course, design Cloud-native systems with virtual machines and containers. Learn to build effective Microservices using technologies like Flask and Kubernetes, and analyze successful patterns in Operations including effective alerts, load testing, and Kaizen. Build a containerized Flask application continuously deployed to a Cloud platform: AWS, Azure, or GCP.
Apply Data Engineering to real-world projects using Cloud computing concepts introduced in the first two courses. Develop Data Engineering applications and use software development best practices, including continuous deployment, code quality tools, logging, instrumentation, and monitoring. Build a serverless data engineering pipeline in a Cloud platform: AWS, Azure, or GCP.
Build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. Develop Machine Learning Engineering applications, use AutoML, and delve into emerging topics in Machine Learning including MLOps, Edge Machine Learning, and AI APIs. Build a Flask web application that serves out Machine Learning predictions.
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