Certified Microservice with AI Specialist (CMAIS) Course
Course Description
The Certified Microservice with AI Specialist (CMAIS) program is aimed to help businesses enhance product capabilities, better interact with customers, and create predictive business strategies through the usage of Microservices. The growth of public cloud services provided by enterprise companies such as Amazon, Microsoft, and Google have put an emphasis on the “as-a-service” business model that allows companies to pick and choose necessary Microservices. The Microservice with AI training on advanced computing with AI explains Microservices, its orchestration and how Machine Learning will be a natural fit for Microservice architecture and container orchestration. Participants will also be able to apply the usage of Dockers and Kubernetes as a containerization solution to enable rapid deployment in the Continuous Integration / Continuous Delivery (CI/CD) pipeline.
Course Objective
The objective of the Certified Microservice with AI Specialist (CMAIS) training on advanced computing with AI explains Microservices, its orchestration and how Machine Learning will be a natural fit for Microservice architecture and container orchestration and to enable participants to leverage on Microservices, management of containerized solutions and automated deployment in the production line.
Skills Acquired
Participants will acquire knowledge on the characteristics of Microservices, its comparison with monolithic style, technology choices, and Microservice architecture. The training will also explain Microservice, its orchestration and how Machine Learning will be a natural fit for Microservice architecture and container orchestration. Participants will be able to containerize application by creating Docker configuration files and use the open-source container orchestration tool Kubernetes, for automating deployment and management of containers.
Importance of Microservice with AI Training
Microservices is considered as the next generation services architecture that addresses the pain points associated with the traditional enterprise Service Oriented Architecture. The global market for Microservices is expected to grow at approx. USD 33 Billion by 2023, at 17% of CAGR between 2017 and 2023. These developments are partly because of the work at companies such as Netflix, Amazon, and e-Bay which have visibly applied Microservices. In fact, these companies have not only adopted Microservices practices, but they have also shared the insights and even tools with the tech community. The growth of public cloud services provided by enterprise companies such as Amazon, Microsoft, and Google have put an emphasis on the “as a service” business model that allows companies to pick and choose necessary Microservices. With advanced cloud computing on AI, businesses can enhance product capabilities, better interact with customers, and create predictive business strategies.
Course Outline
- Unit 1: Micro services architecture
- Unit 2: Containers with Docker and Docker concepts
- Unit 3: DevOps
- Unit 4: Kubernetes
- Unit 5: Kubeflow
- Unit 6: TensorFlow in production – TensorFlow serving
Course Outcome
- Understand the evolution of a software architecture from monolithic to micro services
- Understand micro service architecture and its importance in Machine Learning
- Introduction to the open source Kubernetes by Digital Ocean
- Understand and implement in Kubeflow - The Machine Learning stack for Kubernetes.
- Design and develop a microservice application using Docker and orchestrate using Kubernetes
- Design and develop TensorFlow serving to launch TensorFlow model in production
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