32 hours training
GICT Authorized Training Partner
Intermediate-level Machine Learning Course
Hands-on Labs with ML Tools
Certified Microservices with AI Specialist (CMAIS) Course Description
This CMAIS training program provides learners the necessary skills and knowledge about Microservice with AI training on advanced computing with AI. In this training, participants will 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. It also enables participants to leverage Microservices, management of containerized solutions, and automated deployment in the production line.
Though cloud-based solutions such as software as a service (SaaS) and platform as a service (PaaS) are commonly used service offerings, businesses will also begin to adopt machine learning as a service (MLaaS) into their technology stack for many reasons, the main reason being the need to achieve digital transformation. This GICT - Certified Microservice with AI Specialist (CMAIS) training is designed to pave your way to learning Microservices with AI for enabling businesses to enhance their product capabilities and prospering a great career in the most sought-after fields of today.
In this course, learners will be able to:
- Understand the evolution of a software architecture from monolithic to micro services
- Understand micro service architecture and its importance in Machine Learning
- Learn 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
- Design and demonstrate TensorFlow predictive model microservice
Participants are preferred to have experience in software development, business domain or data/business analysis.
About The Examination
This 4-day intensive training program includes the following assessment components.
Component 1. Written Examination
Component 2. Project Work Component (PWC)
These components are individual based. Participants will need to obtain 70% in both the
components in order to qualify for this certification. If the participant fails one of the
components, they will not pass the course and have to re-take that particular failed
component. If they fail both components, they will have to re-take the assessment.
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.
With this course on Certified Microservices with AI Specialist (CMAIS) credential, you are sure to stay on the upfront of future skills and earn a desirable pay package.
Instructor led Online Training
- 32 hrs (4 days) inclusive of training and exam
- Experienced Subject Matter Experts
- Approved and Quality Ensured training Material
- 24*7 leaner assistance and support
- From Monolithic to Micro services
- Core principles that govern micro service architecture
- Micro services architecture
- Technology choices in micro services
- Case Study: How Netflix scales micro services with application data caching
- Machine Learning as micro service in Python
- Docker vs Virtual Machine
- Docker and Docker concepts
- Docker Architecture
- Deploying micro services using containers
- Orchestration tools
- Securing micro services
- Docker ecosystem in Machine Learning
- DevOps Tool chain
- Docker Compose - A packaging tool for DevOps
- DevOps in Machine Learning
- Continuous integration and delivery for microservice
- Case study- Continuous Integration in Machine Learning
- Kubernetes Architecture
- Kubernetes master-node architecture
- Kubernetes cluster services
- Kube fundamentals
- Kubeflow components
- Deploy TensorFlow model in production
- Introduction to TensorFlow serving
- Steps involved in TensorFlow serving
- TensorFlow serving architecture
Data Mining Engineer
Vinsys follows a focused yet flexible training approach that surely increases the learning potential of learners and improves success rates in certification exams. We have matured over 21 years of our training journey and have a proud history of successfully certifying 750,000+ professionals globally. Our GICT approved trainers and courseware are updated as per the latest industry guidelines to provide the best of learning experience to our students.
Candidates interested for this course are preferred to have experience in software development, business domain or data/business analysis.
This course is designed for 32 hours which is inclusive of training and exam.
In this training, you will learn characteristics of Microservices, its comparison with monolithic style, technology choices, and Microservice architecture. You will also gain expertise in the Microservices orchestration along with the ability to containerize application by creating Docker configuration files and use the open-source container orchestration tool Kubernetes, for automating deployment and management of containers.
AI is gaining all the attention and popularity with modern applications and tools focusing on customer-specific services. So, this course on Microservices with AI is the latest addition in the list of professional certifications and quite a blooming area of growth. With this CMAIS certification, you can make sure to have a credibility to serve the future industry roles.