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Overview

IBM Q²D is a global initiative offering specialized master’s programs in collaboration with top academic institutions. We are offering an advanced 2-year M.Sc Computer Science program specializing in Cloud and DevOps.

S - Vyasa Deemed to be University located inside Sattva Global City, Kengeri,which is a NAAC A+, Category 1 University, would be the first university in India to execute this model of student engagement in partnership with IBM. The program is designed to equip students with cutting-edge skills, real-time exposure, and practical project experience, aligning with future workforce demands.

You've embarked on a cutting-edge master's program, crafted with industry leaders and delivered by IBM subject matter experts in a world-class learning environment.

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Program Benefits Include

A Postgraduate Degree awarded by S-VYASA

An Advanced Certificate Digital Badge from IBM

Advanced Learning Certificate from Cambridge University Press and Assessment

This strategic academic-industry collaboration is designed to equip students with both foundational knowledge and
practical skills in emerging domains, Preparing them for high-impact careers in the digital era.

Campus Location

All programs are conducted at the futuristic S-VYASA Bangalore Campus, located inside Sattva Global City IT Park, Kengeri.

The "IBM ICE Advanced Certificate - Cloud and DevOps" program is a comprehensive program designed to equip learners with the essential knowledge and skills to understand, implement, and manage modern cloud computing and DevOps practices. Spanning approximately 200+ hours, this program covers the fundamentals of cloud computing, containerization and orchestration technologies, the creation and management of CI/CD pipelines, the principles and implementation of Infrastructure as Code, and advanced cloud and DevOps practices including monitoring, optimization, security, and AI/ML workload deployment.

Fee Structure 2025-26

Duration: 2 Years I YEAR II YEAR
Admission Fee 15000 -
Tuition Fee 295000 280000
Other Academic Fee 5200 5200
Total Fee 315200 285200

Program Objectives

Upon successful completion of this program, learners will be able to:

  • Understand the fundamental concepts of cloud computing, including service and deployment models, and the offerings of major cloud providers.
  • Master containerization using Docker for application packaging and isolation.
  • Implement and manage container orchestration using Kubernetes for scalable cloud deployments.
  • Design, build, and manage automated CI/CD pipelines using industry-standard tools.
  • Understand and implement Infrastructure as Code (IaC) using tools like Terraform and Ansible for cloud infrastructure management.
  • Set up comprehensive monitoring and logging solutions for cloud environments.
  • Implement performance optimization techniques for cloud workloads.
  • Apply cloud security best practices to ensure secure deployments.
  • Understand the considerations for deploying and managing AI/ML workloads on cloud platforms.

Program Summary This program is structured into five progressive modules that cover the core aspects of Cloud and DevOps.

Module 1

Introduces the foundational concepts of cloud computing.

Module 2

Focuses on containerization with Docker and orchestration with Kubernetes.

Module 3

Delves into building and managing CI/CD pipelines for automation.

Module 4

Covers the principles and implementation of Infrastructure as Code.

Module 5

explores advanced cloud and DevOps practices including monitoring, optimization, security, and AI/ML on the cloud.

Learning Modules

  • Fundamental concepts of cloud computing.
  • Cloud service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS).
  • Cloud deployment models: Public cloud, private cloud, hybrid cloud, multi-cloud.
  • Key characteristics of cloud computing: On-demand self-service, broad network access, resource pooling, rapid elasticity, measured service.
  • Overview of major cloud providers: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) - basic service categories and offerings.

  • Containerization concepts and benefits.
  • Introduction to Docker: Dockerfiles, images, containers, networking, storage.
  • Hands-on experience with Docker commands and basic Dockerfile creation.
  • Introduction to Kubernetes: Architecture (master-node, worker-node), pods, deployments, services, namespaces.
  • Deploying and managing containerized applications using Kubernetes.
  • Scaling and updating applications in Kubernetes.

  • Principles of Continuous Integration (CI) and Continuous Delivery (CD).
  • Introduction to CI/CD tools: Jenkins, GitLab CI, Azure DevOps (one or more likely emphasized).
  • Designing and building CI/CD pipelines for automated build, test, and deployment processes.
  • Integrating version control systems (e.g., Git) with CI/CD pipelines.
  • Automating software testing within CI/CD pipelines.
  • Deployment strategies to cloud environments (e.g., blue/green, canary).

  • Principles and benefits of Infrastructure as Code (IaC).
  • Introduction to Terraform: Writing Terraform configurations to provision cloud resources (e.g., virtual machines, networks, storage).
  • Introduction to Ansible: Writing Ansible playbooks for configuration management and application deployment.
  • Comparing and contrasting Terraform and Ansible.
  • Automating infrastructure provisioning and management in cloud environments.

Program Outcomes

Upon successful completion of this program, learners will be able to:

  • Explain the fundamental concepts and models of cloud computing.
  • Containerize applications using Docker and orchestrate them with Kubernetes.
  • Design, build, and manage automated CI/CD pipelines using industry-standard tools.
  • Implement Infrastructure as Code using Terraform and Ansible to manage cloud infrastructure.
  • Set up basic monitoring and logging for cloud environments.
  • Understand performance optimization and security best practices for cloud workloads.
  • Identify key considerations for deploying AI/ML workloads on the cloud..

Skills Attained

Upon completion of this program, learners will gain the following skills:

  • Cloud Computing Fundamentals: Understanding cloud models and providers.
  • Containerization with Docker: Packaging and managing applications in containers.
  • Container Orchestration with Kubernetes: Deploying, scaling, and managing containerized applications.
  • CI/CD Pipeline Management: Designing and implementing automated software delivery pipelines.
  • Infrastructure as Code (IaC): Provisioning and managing cloud infrastructure using Terraform and Ansible.
  • Cloud Monitoring and Logging: Setting up basic monitoring and logging solutions.
  • Cloud Performance Optimization: Understanding techniques for improving cloud workload performance.
  • Cloud Security Basics: Applying fundamental security best practices in the cloud.
  • Awareness of AI/ML on Cloud: Understanding key considerations for deploying AI/ML workloads.

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