KSR Datavizon

AIOps (DevOps+AI) & MLOps Engineering Program

Bridge the gap between ML models and production-grade DevOps pipelines

Advance your DevOps and MLOps engineering skills. Learn CI/CD automation, Kubernetes container orchestration, and model versioning tracking with MLflow - taught by senior cloud practitioners.

Curriculum Plan
NASSCOM AffiliatedISO 9001:2015 CertifiedStartup India Recognised
AIOps (DevOps+AI) & MLOps Engineering Program - KSR Datavizon

Our students work at

TCSTCS
InfosysInfosys
WiproWipro
CapgeminiCapgemini
DeloitteDeloitte
IBMIBM
HCLHCL
EYEY
KPMGKPMG
PwCPwC
Tech MahindraTech Mahindra
PersistentPersistent
HexawareHexaware
LTM LimitedLTM Limited
NokiaNokia
TCSTCS
InfosysInfosys
WiproWipro
CapgeminiCapgemini
DeloitteDeloitte
IBMIBM
HCLHCL
EYEY
KPMGKPMG
PwCPwC
Tech MahindraTech Mahindra
PersistentPersistent
HexawareHexaware
LTM LimitedLTM Limited
NokiaNokia
Duration4 MonthsLive Training
ModeOnlineMentor-Led
Next Batch11th July 20267:00 PM IST
Trainer⁠Mr.Manikanta10+ Years Industry Experience
Why Learn

Why AIOps (DevOps+AI) & MLOps Engineering Program?

Why Choose Multi Cloud DevOPS with MLOPS Training?

Master DevOps & MLOps across AWS and Azure

Learn to automate software deployment and machine learning model lifecycles in the cloud.

Build automated CI/CD pipelines

Set up automated testing, integration, and continuous delivery for applications and model training.

Work on real-time industry projects

Implement automated infrastructure provisioning and model monitoring for live production systems.

Learn Docker and Kubernetes orchestration

Package services into lightweight containers and manage automated scaling with Kubernetes clusters.

Gain hands-on experience with Linux, Git, Jenkins & Terraform

Master the industry-standard automation stack to write infrastructure as code.

Monitor models with Prometheus & Grafana

Configure automated alert notifications for model drift and system health in production.

Who Can Learn

Built for engineers & switchers targeting strong outcomes.

Final-year Students

Graduate ready with deployed projects, not just a degree.

Software Developers

Backend or frontend devs ready to upskill.

Data Analysts

Already use SQL & Excel? Level up to advanced engineering.

Career Switchers

Non-tech professionals planning a complete pivot into technology.

Working Professionals

Upskill in evenings & weekends, with full LMS access for revision.

Systems Administrators

Transition from manual server maintenance to writing Infrastructure-as-Code.

About the Course

Structured, project-based learning.

Go beyond passive video playlists. Learn through mentor-guided coding sprints designed to build real-world engineering skills.

16-Week Structured Sprints

Over 16 weeks of live, mentor-led training, you will move from fundamentals to advanced concepts through hands-on project sprints.

100% Live Practice & Feedback

Sessions are 100% online and live - taught personally by industry practitioners. Every week ends with an assignment reviewed and graded by your mentor.

End-to-End Career Support

Career support continues until you land your first interview call. We help with LinkedIn & Naukri profile building, resume writing, mock interviews, and corporate etiquette.

Live Learning Session Illustration
OUTCOMES
What you walk away with
  • Course Completion Certificate
  • LinkedIn & Naukri profile building
  • ATS-friendly resume preparation
  • Support till you get interview calls
  • Interview prep - tips & tricks
  • Soft skills & corporate etiquette
  • 365 days of LMS & recordings access
03Meet Your Trainer

Taught by active practitioners.

Lead Trainer · AIOps (DevOps+AI) & MLOps Engineering Program
⁠Mr.Manikanta

Industry expert with over 10 years of experience shipping production applications.

11+Years Industry
1,600+Mentees Trained
LiveOnline Sessions
4.7Trainer Rating
04Tools & Frameworks

The stack you use on the job.

Work confidently using industry platforms across core deployment targets.

Linux
Git & GitHub
Cloud Computing
AWS
Microsoft Azure
Infrastructure as Code (IaC)
Terraform
Ansible
CI/CD Pipelines
Jenkins
Docker
Kubernetes
GitOps
Argo CD
SRE
Observability
Prometheus
Grafana
MLOps
MLOps
MLflow
Kubeflow
Curriculum Plan

Step-by-step curriculum roadmap.

Progress logically from foundational concepts to advanced, production-ready engineering skills.

01
LINUX
Linux Essentials
Linux Basics File System & Permissions Process Management Networking Basics Shell Scripting Automation Scripts
02
GIT-GITHUB
Git & GitHub
Git Basics Branching & Merging Pull Requests & Code Reviews Git Workflows GitHub Actions Overview
03
CLOUD-FUNDAMENTALS
Cloud Fundamentals (AWS & Azure)
Cloud Computing Models IAM & RBAC AWS Core Services (EC2, S3, RDS) Azure Core Services (VMs, Storage, Azure SQL) Monitoring Basics
04
IAC-CONFIGURATION
Infrastructure as Code & Configuration Management
Terraform Basics HCL & Providers Terraform Workflows Ansible Architecture Playbooks & Roles Terraform + Ansible Integration
05
CICD-JENKINS
CI/CD with Jenkins
Jenkins Architecture Jobs & Pipelines Declarative vs Scripted Pipelines CI/CD Pipeline Design Jenkins Integration with Git
06
KUBERNETES
Docker & Kubernetes
Docker Fundamentals Kubernetes Architecture Pods, Deployments & Services ConfigMaps & Secrets Ingress & Autoscaling Kubernetes Storage
07
GITOPS-SRE
GitOps, SRE & Observability
GitOps Principles Argo CD SRE Concepts (SLI, SLO, SLA) Monitoring with Prometheus & Grafana Logging & Tracing Incident Management
08
MLOPS
MLOps & Model Deployment
MLOps Lifecycle Experiment Tracking (MLflow / W&B) Model Versioning CI/CD for ML Pipelines Model Deployment on Kubernetes Monitoring Model Drift Capstone MLOps Project
08Outcomes

Target industry positions directly.

12,900+ jobs

MLOps Engineer

12 - 28 LPA

Automate model deployment, registry, and drift monitoring.

25,400+ jobs

DevOps Engineer

8 - 22 LPA

Maintain CI/CD pipelines, Docker networks, and Kubernetes clusters.

14,100+ jobs

Cloud Automation Engineer

10 - 24 LPA

Deploy configurations dynamically using Terraform.

8,200+ jobs

Release Engineer

9 - 20 LPA

Coordinate software build delivery pipelines.

11,300+ jobs

Site Reliability Engineer (SRE)

12 - 28 LPA

Monitor application availability and configure alerts.

9,800+ jobs

Platform Engineer

11 - 26 LPA

Build developer tools and maintain cloud clusters.

30,000+
MLOps & DevOps Active Listings
₹11 - 25 LPA
Average MLOps Engineer Salary
32% YoY
Increase in AI Infrastructure Roles
78%
Companies Scaling ML to Production
Alumni Actions

Real reviews from successful students.

Join a thriving network of industry professionals. Read what our graduates say about their career transformation journey.

Manikanta sir explained Docker and Kubernetes beautifully. Setting up CI/CD pipelines with Jenkins and deploying MLflow models on Kubernetes cluster was something I could directly talk about during my interviews.

V
Vikas Patel
MLOps Engineer · Capgemini
DevOps to MLOps switch

Managing model drift and setting up Prometheus and Grafana for monitoring model performance was exactly what my current project required. Very practical and no fluff.

S
Shweta Sen
DevOps Engineer · HCLTech
+60% Salary Hike

The course bridged the gap between ML models and DevOps pipelines. We set up automated model registry in MLflow and triggered Jenkins pipelines for redeployment.

D
Deepak R.
Cloud Automation Engineer · Wipro
Career Transition

Manikanta sir explained Docker and Kubernetes beautifully. Setting up CI/CD pipelines with Jenkins and deploying MLflow models on Kubernetes cluster was something I could directly talk about during my interviews.

V
Vikas Patel
MLOps Engineer · Capgemini
DevOps to MLOps switch

Managing model drift and setting up Prometheus and Grafana for monitoring model performance was exactly what my current project required. Very practical and no fluff.

S
Shweta Sen
DevOps Engineer · HCLTech
+60% Salary Hike

The course bridged the gap between ML models and DevOps pipelines. We set up automated model registry in MLflow and triggered Jenkins pipelines for redeployment.

D
Deepak R.
Cloud Automation Engineer · Wipro
Career Transition

Manikanta sir explained Docker and Kubernetes beautifully. Setting up CI/CD pipelines with Jenkins and deploying MLflow models on Kubernetes cluster was something I could directly talk about during my interviews.

V
Vikas Patel
MLOps Engineer · Capgemini
DevOps to MLOps switch

Managing model drift and setting up Prometheus and Grafana for monitoring model performance was exactly what my current project required. Very practical and no fluff.

S
Shweta Sen
DevOps Engineer · HCLTech
+60% Salary Hike

The course bridged the gap between ML models and DevOps pipelines. We set up automated model registry in MLflow and triggered Jenkins pipelines for redeployment.

D
Deepak R.
Cloud Automation Engineer · Wipro
Career Transition

Manikanta sir explained Docker and Kubernetes beautifully. Setting up CI/CD pipelines with Jenkins and deploying MLflow models on Kubernetes cluster was something I could directly talk about during my interviews.

V
Vikas Patel
MLOps Engineer · Capgemini
DevOps to MLOps switch

Managing model drift and setting up Prometheus and Grafana for monitoring model performance was exactly what my current project required. Very practical and no fluff.

S
Shweta Sen
DevOps Engineer · HCLTech
+60% Salary Hike

The course bridged the gap between ML models and DevOps pipelines. We set up automated model registry in MLflow and triggered Jenkins pipelines for redeployment.

D
Deepak R.
Cloud Automation Engineer · Wipro
Career Transition
Career Launch

Placement networks that act actively.

Our active alumni ecosystem supports you with live workshops, direct placement updates, and mock practice panels until you get hired.

200+
Hiring Partners
85%
Avg. Salary Hike
2,400+
Mentees Placed
6 wks
Avg. Time to Offer
01
Resume & Portfolio Review

ATS-friendly resume rewrite, GitHub audit, and capstone project documentation review.

02
LinkedIn & Naukri Optimisation

Profile rebuild with recruiter-targeted keywords, headline crafting, and weekly content tips.

03
Mock Interviews

Two structured mocks: one technical (live coding + system design), one HR/behavioural.

04
Recruiter Connections

Curated job openings and direct intros via our network of 200+ hiring-partner companies.

05
Soft Skills & Etiquette

Communication, client handling, and corporate-readiness coaching from senior practitioners.

06
Lifetime Alumni Access

Slack community, referral pipeline, and ongoing peer support - useful long after placement.

Priority Enrollment Open

Secure your seat for the upcoming batch.

Talk to our team about flexible pacing, project options, and scheduling before you enroll.

Frequently Addressed Inquiries
What is the duration of the AIOps & MLOps course?
4 months of live online training, with 365 days of LMS access.
What is the difference between DevOps and MLOps?
DevOps focuses on automating traditional software deployment. MLOps extends this to automate the lifecycle of machine learning models, including training, versioning, and monitoring.
What orchestration and automation tools will I learn?
Linux, Git, Jenkins, Terraform, Docker, Kubernetes, Prometheus, Grafana, MLflow, and cloud services on AWS/Azure.
Who is the ideal candidate for this course?
Software engineers, systems administrators, cloud engineers, and data scientists looking to specialize in cloud automation and machine learning operations.
Enroll Now
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