Courses and programs

Structured programs for Cloud, DevOps, Kubernetes, AI, MLOps, and automation careers.

Each program is designed with practical projects, career outcomes, and mentor-led support.

Batch FormatsUpcoming, ongoing, weekend, corporate, online live

Learning StyleMentor-led, practical, project-focused

AudienceStudents, freshers, professionals, career switchers

Program catalog

Filter by skill level and choose the right learning path.

Beginner to Intermediate

AWS Cloud Engineer Program

Duration: 10 weeks | Batch: Weekend and online live

Prerequisites: Basic networking and Linux awareness.

Tools covered

AWS core services, IAM, VPC, EC2, S3, RDS, CloudWatch, Route 53, and cost awareness.

Learning outcomes

Design basic cloud architecture, operate cloud workloads, and prepare for cloud engineer roles.

Intermediate

DevOps Engineering Program

Duration: 12 weeks | Batch: Weekend and corporate training

Prerequisites: Linux basics and one scripting language preferred.

Tools covered

Git, GitHub, Jenkins, Terraform, Docker, monitoring, CI/CD, and release management.

Learning outcomes

Build reliable delivery pipelines, automate infrastructure, and understand modern operations.

Advanced

Kubernetes and Containerization

Duration: 8 weeks | Batch: Online live

Prerequisites: Docker and Linux basics.

Tools covered

Docker, Kubernetes, cluster operations, deployments, services, ingress, observability, and production patterns.

Learning outcomes

Deploy and operate containerized applications with Kubernetes confidence.

Beginner Friendly

AI and LLM Foundations

Duration: 6 weeks | Batch: Mentor-led sessions

Prerequisites: Curiosity and basic computer literacy.

Tools covered

AI concepts, LLMs, prompt engineering, AI integrations, use cases, and responsible AI basics.

Learning outcomes

Understand AI workflows and build simple AI-assisted solutions.

Advanced

MLOps and AI Infrastructure

Duration: 10 weeks | Batch: Upcoming

Prerequisites: Python, ML basics, and cloud awareness.

Tools covered

Model deployment, lifecycle management, monitoring, pipelines, and AI infrastructure.

Learning outcomes

Support machine learning systems from experiment to production operations.

Beginner

Linux and Automation

Duration: 6 weeks | Batch: Ongoing

Prerequisites: None.

Tools covered

Linux, shell scripting, Git, Python for DevOps, security basics, and automation fundamentals.

Learning outcomes

Build a strong foundation for Cloud, DevOps, and platform engineering paths.

What every course includes

Designed for practical learning and career readiness.

Curriculum Overview

Clear modules, learning milestones, tools covered, hands-on activities, and outcomes for each course.

Instructor Guidance

Mentor-led sessions with industry context, practical examples, and career direction.

Hands-on Projects

Realistic assignments and projects that help learners explain their work with confidence.

Batch Timings

Support for upcoming, ongoing, weekend, corporate, and online live learning schedules.

Prerequisite Clarity

Know exactly what background is needed before joining a beginner, intermediate, or advanced batch.

Learning Outcomes

Every program is connected to role readiness, confidence, and continued upskilling.

Tools and technologies

Learn the modern tools expected in real IT teams.

AWSDockerKubernetesJenkinsTerraformGit and GitHubLinuxShell scriptingPython for DevOpsObservability toolsSecurity basicsFinOps awareness

Not sure which program to choose?

Start with career guidance and find the right batch for your goal.

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