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Cohort 015 · Engineering Track · Enrolling Now

DevOps with AI
& AI Agents

Transform IT operations with AI DevOps agents. Master AWS, Azure, Kubernetes, and Terraform — then build the AI agents that watch pipelines, triage alerts, and ship code on your behalf. 3 months. One production capstone. A job offer, not a certificate.

3mo
duration
40+
modules
4.7/5
cohort rating
500+
reviews
Where our DevOps alumni work
MicrosoftAmazonSalesforceServiceNowDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL MicrosoftAmazonSalesforceServiceNowDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL
What you leave with

Four things every DevOps grad walks away with.

Most programs hand you a certificate and a Zoom recording. Ours hands you a running system, a portfolio, and an interview.

01
Agent-Ready skills
Build, deploy, and monitor AI agents that run production workflows — not chatbot toys.
02
A shipped capstone
A live CI/CD pipeline on EKS, monitored, instrumented, and accessible on a public URL.
03
Verifiable credential
2026 Agent-Ready rubric, graded 1–5 with a public verification URL recruiters can check.
04
Direct placement pipeline
GitHub + LinkedIn rewrite, resume rebuild, and warm intros to our 1,000+ hiring partners.
12 weeks, four phases

The path from "knows what CI/CD is" to ships AI-Ops agents.

Weeks 1–3 build the base. Weeks 4–7 ship the pipeline. Weeks 8–10 layer observability and AI. Weeks 11–12 are the capstone.

WEEKS 1–3 · FOUNDATIONS

Linux, Git, Cloud Basics

  • Linux CLI, shell scripting, file permissions
  • Git, GitHub flow, pull requests, webhooks
  • AWS EC2, VPC basics, IAM
  • Azure VMs, core services, RBAC
YOU SHIPAn automated server-bootstrap script that launches EC2 + Azure VM with a single command.
WEEKS 4–7 · THE PIPELINE

CI/CD · Docker · Kubernetes · Terraform

  • Jenkins + GitHub Actions (Pipelines-as-Code)
  • Dockerize a 3-tier LMS application
  • K8s: Deployments, Services, Ingress, Secrets
  • Terraform-provisioned EKS cluster
YOU SHIPA full CI/CD pipeline deploying the LMS to an EKS cluster you provisioned with Terraform.
WEEKS 8–10 · OBSERVABILITY + AI

Prometheus, Grafana, Cursor, Agents

  • Prometheus metrics + PromQL queries
  • Grafana dashboards + AlertManager
  • Cursor AI for infra code generation
  • LangGraph 1.0 + MCP for agent workflows
YOU SHIPA Prometheus + Grafana stack watching your cluster, with an AI agent that triages alerts automatically.
WEEKS 11–12 · CAPSTONE

Deploy an AI-Ops agent into a real partner org.

Pick a real partner problem — noisy alerts, slow rollbacks, flaky deploys. Build an AI agent that fixes it. Deploy to their Salesforce or ServiceNow tenant. Walk out with a production artifact, a reference, and often, an offer letter.

Partner orgs (2026)48
Capstones deployed180+
→ Placement offers78%
Course curriculum

Six sections. 50+ modules. Every one maps to something you'll ship.

Jump to any section on the left. Click a module to see topics, hands-on lab, and key technologies.

01

Fundamentals of IT & AI

The ground floor: how applications actually work, how teams ship them, and where AI fits in the 2026 stack. You leave this section fluent in the vocabulary of any engineering org.
5 MODULES
~ WEEK 1
What is an Application & types
Web application fundamentals
Frontend: HTML, CSS, JavaScript, React
Backend: Python, Java, Node.js
Databases: MySQL, PostgreSQL, MongoDB
SDLC phases end-to-end
Waterfall vs. Agile
Scrum roles, events, artifacts
User stories, epics, themes
Acceptance criteria, estimation
Backlog management
Tools: Google Sheets, Azure Boards
TOOLSAzure BoardsJiraSheets
Computing power & CPU/GPU
Intro to cloud computing
IaaS, PaaS, SaaS
Service model tradeoffs
What is AI & how it works
ML fundamentals
Deep learning fundamentals
Generative AI & LLMs
Image generation models
AI in everyday learning
CRM & HRMS landscapes
Retail & E-Commerce
Healthcare applications
Where DevOps lives in each
02

Core & Advanced DevOps

The backbone of the program. Twelve modules that take you from "runs my own Linux server" to "ships a GitOps pipeline on Kubernetes" — plus a Cursor AI module for agent-assisted DevOps workflows.
12 MODULES
WEEKS 2–7
DevOps culture & practices
The DevOps infinity loop
Server types (Web, DB, App)
Cloud intro: AWS & Azure
Networking: VPC, Security Groups
Launch & configure EC2 + Azure VMs
STACKAWS EC2Azure VMVPC
Linux file system & navigation
CLI commands & user management
File permissions (chmod, chown)
APT package management
Shell scripting for automation
Hands-on: web-server deploy script
STACKUbuntuBashvim
Git architecture: WD / Staging / Repo
add, commit, push, pull
Branching & merging strategies
Resolving merge conflicts
PRs & code reviews
GitHub webhooks for automation
STACKGitGitHubWebhooks
3-tier application architecture
PostgreSQL setup & management
Node.js + Express backend
ReactJS frontend
NGINX web server
Ship: complete LMS deployment
STACKPostgreSQLNodeReactNGINXPM2
Jenkins install & configuration
Freestyle & Pipeline jobs
Master-Worker architecture
Jenkinsfiles (Pipeline-as-Code)
SonarQube static analysis
Nexus artifact management
STACKJenkinsSonarQubeNexus
Containers vs VMs
Monolithic vs Microservices
Docker architecture
Networking: bridge / host / overlay
Dockerfiles & multi-stage builds
docker-compose & Docker Hub
STACKDockerComposeDocker Hub
K8s architecture: Master & Workers
Pods, Deployments, Services
ConfigMaps & Secrets
Persistent storage & PVCs
Ingress controllers & routing
Auto-scaling & rolling updates
STACKKubernetesHelm
EKS cluster architecture
Node groups & scaling
AWS Load Balancer Controller
EKS networking & IAM roles
Cost optimization strategies
Ship: LMS on production EKS
STACKAWS EKSALBIAM
IaC concepts & workflow
HCL basics & providers
Resources, variables, outputs
State management
Modules & remote state (S3 + DynamoDB)
Workspaces & best practices
STACKTerraformHCLS3DynamoDB
Observability pillars
Prometheus data model & PromQL
Service discovery & exporters
AlertManager rules
Grafana dashboards
K8s monitoring & instrumentation
STACKPrometheusGrafanaAlertManager
Workflow syntax & structure
Events, jobs, steps
Hosted vs self-hosted runners
Secrets & environment vars
Matrix builds & artifacts
Docker build & K8s deploy
STACKGitHub ActionsDockerK8s
AI-assisted development
Cursor AI features & capabilities
AI pair programming for DevOps
Generate shell, Dockerfiles, K8s manifests
Terraform code generation
Debug & troubleshoot with AI
STACKCursorCopilotClaude
03

Azure DevOps (ALM)

The Microsoft stack for end-to-end ALM. Five modules covering Boards, Repos, Pipelines, Artifacts, and Test Plans — for the enterprise roles where Azure DevOps is the standard.
5 MODULES
WEEK 8
Azure DevOps ecosystem
Boards, Repos, Pipelines overview
Creating your first pipeline
Integration landscape
Work items, sprints, scrum features
Connecting Boards to GitHub
Managing backlogs
Board integrations
Azure Repos fundamentals
Branches & cloning
Import code from GitHub
Code search in Repos
Deployment strategies
CI triggers & YAML basics
Setting up CI builds
Adding tests to the pipeline
Agents & tasks
STACKAzure PipelinesYAML
Packages in Azure Artifacts
Feeds & views
Artifacts → Pipelines integration
Azure Test Plans basics
Testing web apps
04

AWS & Azure Cloud

Deep cloud fluency across both majors. AWS compute, networking, storage, cost; Azure compute, storage, networking, governance, app services. Certification-prep rigor, without the slide-deck pedagogy.
10 MODULES
WEEK 9
Global infrastructure & pricing
Account setup & billing
IAM users, roles, policies
AWS CLI install & config
CloudWatch & CloudTrail
EC2 launch & instance types
Auto Scaling Groups
Elastic Load Balancing
Lambda & serverless
API Gateway with Lambda
STACKEC2ALBLambdaAPI GW
VPC, subnets, route tables
Internet gateways
KMS encryption
Cognito user pools
Security best practices
S3 buckets & permissions
Versioning & lifecycle policies
EBS volume management
Cost Explorer & Budgets
Trusted Advisor
Savings Plans
IaaS / PaaS / SaaS
Public / Private / Hybrid
Cloud tradeoffs & when
Azure compute types
Storage options
Virtual networks & subnets
Azure database services
Azure pricing & cost mgmt
Support plans
RBAC, resource locks, Policy
Portal vs CLI
Azure Monitor
Resource Manager & Policy
App Service plans
Networking for App Service
Container images
Deploy web apps & APIs
05

Python for AI & DevOps

Python depth that pays off everywhere — from shell scripts to agent tools. OOP, data structures, generators, decorators, and the packages that actually ship: requests, pandas, numpy.
10 MODULES
WEEK 10
Setup & VS Code
Syntax, keywords, identifiers
Variables & memory
Data types & conversion
Operators & conditionals
Loops, range(), control flow
Indexing & slicing
f-strings & formatting
Immutability
Search, check, trim methods
List creation & operations
append, insert, pop, remove
Sorting & comprehensions
Tuple packing/unpacking
Dict creation & methods
Dict comprehensions
Set ops: union, intersection
Frozen sets
Counter, defaultdict, deque
Custom iterators
Generators & yield
map, filter, reduce
Positional, keyword, default args
*args, **kwargs
Local & global scope
Recursion & lambdas
Built-in & external modules
Package structure & __init__
pip & requirements.txt
requests, pandas, numpy
File modes & operations
Directory management
CSV reader/writer
JSON dump/load
try/except/finally
Custom exceptions
Decorators in depth
Context managers
Classes & objects
4 pillars: encap / inherit / abstract / poly
super() & MRO
Magic methods
Abstract base classes
06

Generative & Agentic AI

The AI-native part. LLMs, RAG, LangChain 1.0, LangGraph, MCP, A2A, HITL, observability with LangSmith. Not theory — the stack you'll use to build your capstone agent.
10 MODULES
WEEKS 11–12
LLM fundamentals
Transformer architecture
GPT, Claude, Gemini, DeepSeek
Tokenization
Model selection by use case
Cost optimization
Advanced prompting
Reasoning modes
Reducing hallucinations
Chain-of-thought
Multimodal prompting
OpenAI, Anthropic, Google, DeepSeek APIs
create_agent abstraction
Middleware systems
Function calling & structured outputs
STACKLangChainOpenAIAnthropic
ChromaDB, Pinecone, Qdrant
Production RAG pipelines
Agentic RAG & self-improving retrieval
Hybrid search
Hallucination reduction
STACKPineconeChromaDBQdrant
Streamlit & Gradio interfaces
LangGraph Platform deployment
EU AI Act compliance
Monitoring & observability
Agentic fundamentals (plan, reason, act)
LangChain 1.0 Agents with middleware
Model Context Protocol (MCP)
Enterprise use cases
LangGraph architecture
State management & graph logic
Node caching
Pre/post hooks for guardrails
Parallel execution & deferred nodes
Conditional routing
Iterative refinement loops
Quality-gated content generation
Durable state management
Postgres & Redis persistence
HITL implementations
Multi-day workflows
LangGraph Platform deployment
Multi-agent design
Google A2A protocol
LangSmith observability
Prompt injection prevention
Agent guardrails & safety
STACKLangGraphLangSmithA2AMCP
Tools you'll master

24 tools, one production capstone.

Not a shallow tour. You'll use every one of these in at least one graded exercise.

L
Linux
G
Git
GH
GitHub
J
Jenkins
D
Docker
K
Kubernetes
T
Terraform
A
Ansible
P
Prometheus
Gr
Grafana
S
SonarQube
N
Nexus
aws
AWS
Az
Azure
NX
NGINX
Py
Python
Pg
PostgreSQL
Nd
Node.js
C
Cursor AI
LC
LangChain
LG
LangGraph
LS
LangSmith
M
MCP
VD
Vector DBs
Real-time projects

You don't watch videos. You ship software.

Three full-production projects, each threaded through the entire curriculum. By the capstone, you've built the whole stack around them.

Hero project · weeks 3–12

LMS on EKS

Full LMS: course authoring, learner tracking, assessments — deployed to production EKS via a Jenkins + GitHub Actions pipeline, with an AI tutor agent backing the content engine.

ReactNodePostgresEKSTerraformLangGraph
View project →
Enterprise · weeks 6–10

HRMS pipeline

CI/CD for an HRMS platform — payroll, onboarding, performance — with an onboarding agent that provisions access on day one.

Azure PipelinesDockerAgentforce
Customer · weeks 8–11

CRM observability

Sales + support CRM with a Prometheus/Grafana stack and an escalation agent that reads tickets and drafts refund PRs.

GrafanaLangSmithServiceNow
Capstone · weeks 11–12

Your AI-Ops agent, in a real partner org.

Pick a real partner problem. Ship an AI agent into their tenant. Walk away with a production artifact, a reference, and often, an offer letter.

2026: 180+ deployed78% → placement offers
See capstone gallery →
Your instructor

Taught by the engineer who ran your dream job's pipelines.

Not a career trainer. A practitioner who still ships code.

AS
Ahmed Srinivasan
Lead Instructor · DevOps & AI Agents
AWS · CKA · HashiCorp · LangChain
"DevOps isn't scripts anymore. It's an agent reading your alerts at 3 AM, opening the PR, and waking you up only when it matters. We teach you to build that."
11 yrs
DEVOPS
2,400+
LEARNERS
4.9 /5
RATING

Ahmed came up through ops at an Indian unicorn before leading cloud platform teams across three continents. He's built CI/CD pipelines for a retail chain with 1,200 stores, migrated a bank's monoliths to Kubernetes, and — most recently — shipped the first LangGraph-based AI-Ops agent into production at a Fortune-500 insurer.

His cohorts get two things other programs don't give you: a real engineer who still ships code, and a curriculum rewritten every quarter to match what hiring managers actually ask about.

FAQ

Questions we actually get — answered honestly.

If the answer you need isn't here, book a 20-minute advisor call. No-slides, no-pitch — just your questions.

No. About 40% of our DevOps cohort comes from non-CS backgrounds — mechanical, electrical, commerce. The first three weeks are foundations on purpose. What you do need: comfort with a terminal and ~15 hours/week for three months.
Plan for 12–15 hours: 2 live classes × 2 hours, 1 lab × 3 hours, and roughly 5 hours of asynchronous project work. Weekends are optional office hours with the TA team.
Yes. Every student gets a dedicated placement advisor from week 8 onwards — not a helpdesk. They review your resume, redo your LinkedIn, mock-interview you, and make direct warm introductions to our 1,000+ hiring partners. We track individual outcomes, not cohort averages.
Full refund within 7 days of cohort start, no questions. Pro-rata refund through week 4 if the program isn't working for you. We'd rather refund than have an unhappy alum.
You actually build. Modules 2.12 and all of Section 6 are hands-on — you'll ship a Cursor-assisted Terraform setup, a LangGraph workflow, a RAG pipeline, and your capstone AI-Ops agent. Nothing in the AI track is theory-only.
You get the Agent-Ready 2026 credential, graded on a 1–5 band with a public verification URL. It's co-branded with our partner ecosystem (Salesforce Partner + ServiceNow), and it names the specific capstone artifact you deployed. Recruiters can verify in 10 seconds.
All three. On-campus at our Hyderabad flagship; online cohorts on IST and PST; weekend cohorts for working professionals. Every format ships the same three projects and the same capstone.
We'd rather pause your cohort than push you through. You can freeze your seat for up to 90 days and rejoin the next cohort without paying again. TAs run catch-up sessions every Saturday for anyone more than one week behind.

Cohort 015 starts 12 May 2026.
48 seats. 11 already claimed.

Book a 20-minute advisor call. We'll walk through the curriculum, match it to your current role, and show you two real capstones from cohort 014.

₹89,000
₹1,20,000
25% off · EARLY BIRD
3 MONTHS · STARTS 12 MAY · 48 SEATS · 11 CLAIMED

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