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Industry-Relevant Modules

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Internship Accelerator

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Real-World Projects

College Students
Executive Summary

Your Shortcut from College to Dream Internship & Job

Stop relying on a outdated syllabus. Get real, hands-on Cloud & AI skills that top employers are hiring for — with live projects, industry mentors, and a clear path to your first internship.

Master Cloud Computing, Microsoft Azure, AWS, AI, DevOps, Cybersecurity and Career Readiness — on real enterprise tools and live cloud environments, not simulators.

Internship-First Training Approach
Industry-Ready Practical Skills
Live Enterprise Cloud Environments
Resume & Interview Preparation
Real-World Project Portfolio
Our Mission

Bridge the College-to-Career Gap

Every year, thousands of engineering graduates leave college with degrees but without the practical skills companies are hiring for. Our mission is to close that gap — with real training, real tools, and real outcomes.

The Challenge — What's Broken
  • Outdated syllabus — College curriculum lags 2-3 years behind industry; students learn theory that's no longer relevant
  • Zero practical cloud exposure — Most colleges have no cloud labs; students graduate without ever touching Azure or AWS
  • Empty resumes, no portfolio — No real projects means no interview calls; 83% of graduates go unplaced or underemployed
  • No internship pathway — Students don't know what skills to build or how to land that first internship; companies won't hire without experience
83%

Graduates Unplaced

71.5%

Qualified but Not Hired

2-3 Yrs

Syllabus Lag

Our Solution — How We Fix It
  • Industry-aligned curriculum — Every module is built around what employers actually ask in interviews and job descriptions — Cloud, AI, DevOps, Cybersecurity
  • Hands-on live cloud labs — Not simulators. Every student gets real Azure & AWS environments to build, deploy, and troubleshoot just like on the job
  • Portfolio-worthy real projects — Students leave with 6+ production-grade projects on their resume — cloud infra, CI/CD pipelines, AI deployments — proof of skill, not just a certificate
  • Internship-first career track — From day one, we train for the goal: land a paid internship. Resume building, mock interviews, industry connect — built into every program
100%

Hands-On Practical

6-8 Wk

Internship Accelerator

6+

Real Projects Built

This isn't another coaching center. This is a career launchpad built by an industry professional who has been in the enterprise cloud trenches — not a teacher who's never deployed to production.

See How We Build Job-Ready Skills
Market Opportunity

The Industry Gap We Solve

83% of engineering graduates are unplaced. Why? College syllabus alone won't get you an internship or job. We bridge the gap with real, hands-on industry training.

Current Problems in Education

  • Lack of practical cloud experience
  • No hands-on infrastructure knowledge
  • Zero AI tool exposure
  • No real-world deployment understanding
  • Missing interview preparation
  • No industry project experience
  • Outdated theory-focused curriculums

What Industry Demands

  • Cloud Computing skills (Azure & AWS)
  • Artificial Intelligence & ML proficiency
  • Cybersecurity fundamentals
  • DevOps & CI/CD pipeline knowledge
  • Infrastructure Engineering
  • Certification readiness
  • Practical, project-based experience
Who We Serve

Target Audience

Built specifically for college students hungry for real skills, paid internships, and job-ready confidence — not just another certificate.

Engineering Students

B.E. / B.Tech students who want practical skills that land paid internships & jobs

BCA / B.Sc. Students

CS/IT graduates who need real industry exposure beyond the textbook

Diploma Students

Polytechnic students looking to build job-ready IT infrastructure skills

Working Professionals

IT pros & career switchers wanting hands-up, not just theory-up

Industry-Aligned Courses

Practical Courses That Get You Hired

Each course maps directly to your VTU syllabus — but replaces theory with hands-on cloud labs, real projects, and internship-ready skills. Max 6 weeks each.

VTU: Cloud Computing (Sem 6) · Computer Networks (Sem 5)

Cloud Engineering & Infrastructure

6 Weeks Intermediate

Go from zero cloud exposure to building production-grade infrastructure on Azure & AWS. Covers everything IAM, networking, compute, storage, HA/DR, and IaC — the exact skills cloud engineering interns use daily.

  • Week 1 — Cloud Foundations & IAM: Azure vs AWS overview, Portal/Console navigation, IAM users/groups/roles/policies, MFA, least privilege — Lab: Set up multi-account structure with RBAC
  • Week 2 — Compute & Storage: EC2 vs Azure VMs, instance families, sizing, spot vs reserved; S3 vs Blob Storage, lifecycle policies, versioning, encryption — Lab: Deploy a VM with attached storage, configure backups
  • Week 3 — Cloud Networking: VPC, subnets, route tables, internet gateway, NAT, security groups vs NACLs, VPC peering, VPN — Lab: Design a multi-tier VPC with public/private subnets
  • Week 4 — Load Balancing & Auto-Scaling: ALB vs NLB vs Azure Load Balancer, target groups, health checks, launch templates, auto-scaling policies — Lab: Deploy a scalable web app behind ALB with auto-scaling
  • Week 5 — Databases, Monitoring & HA: RDS vs Azure SQL, read replicas, backups; CloudWatch vs Azure Monitor, dashboards, alarms; multi-AZ deployment, DR strategies — Lab: Set up monitoring and disaster recovery for production app
  • Week 6 — Infrastructure as Code & Capstone: Terraform basics — resources, variables, state, modules; deploy full 3-tier architecture with IaC — Capstone: Deploy and monitor a production-ready 3-tier web application
You Build

Production-ready 3-tier web architecture on AWS/Azure with auto-scaling, monitoring, IaC, and HA — portfolio centerpiece for cloud intern applications

AZ-900 · AWS CCP Aligned Cloud Engineer · DevOps · SRE
VTU: DevOps Lab (Sem 6) · Software Engineering (Sem 5)

DevOps & CI/CD Pipeline Engineering

5 Weeks Intermediate

Master the DevOps workflow that powers every modern tech team. From Git branching strategies to Docker containers, Kubernetes orchestration, and automated CI/CD pipelines — this is what "DevOps Lab" should actually teach.

  • Week 1 — Git & Agile Practices: Branching strategies (GitFlow, trunk-based), pull requests, code reviews, squash merges; Scrum events, sprint planning, standups — Lab: Set up GitHub repo with branch protection, project board, and PR workflow
  • Week 2 — Docker & Containerization: Images vs containers, Dockerfile writing, multi-stage builds, Docker Compose, container registries (Docker Hub, ACR) — Lab: Containerize a Node.js + MongoDB app with Docker Compose
  • Week 3 — CI/CD Pipelines: GitHub Actions / Azure DevOps — triggers, jobs, steps, environments, secrets, artifacts; build → test → deploy workflow — Lab: Build a CI/CD pipeline that auto-deploys on every git push
  • Week 4 — Kubernetes Fundamentals: Pods, deployments, services, ConfigMap, secrets, ingress, namespaces; kubectl commands — Lab: Deploy containerized app on Kubernetes cluster with ingress and scaling
  • Week 5 — Monitoring & Capstone: ELK stack setup, log aggregation, dashboards; Prometheus + Grafana basics — Capstone: Build complete pipeline: code push → CI/CD → containerize → deploy on K8s → monitor with ELK
You Build

End-to-end DevOps pipeline: Git → CI/CD → Docker → Kubernetes → Monitoring. A full production deployment workflow you can demo in any interview

Certified Kubernetes (CKA) Aligned DevOps Engineer · Platform Engineer
VTU: Generative AI Lab (Sem 6) · ML (Sem 6)

Generative AI & LLM Applications

4 Weeks Beginner-Friendly

VTU just introduced the Gen AI Lab — but no one knows how to teach it. This course fills that gap completely. Learn prompt engineering, build RAG pipelines, deploy LLM apps with LangChain, and understand AI safety — all on Azure OpenAI.

  • Week 1 — LLM Foundations & Prompt Engineering: How LLMs work, tokens, temperature, system vs user prompts; prompt techniques — few-shot, chain-of-thought, persona prompting, structured outputs — Lab: Build a prompt library with OpenAI API
  • Week 2 — RAG Architecture & Vector Databases: Retrieval-Augmented Generation, embeddings, semantic search, chunking strategies; vector DBs (FAISS, Chroma) — Lab: Build a RAG pipeline that answers questions from your own documents
  • Week 3 — LangChain Framework & AI Agents: Chains, routers, memory, tools, agents; multi-step reasoning, tool-use patterns, OpenAI function calling — Lab: Build a LangChain agent that can query databases, search web, and generate reports
  • Week 4 — Deployment, Security & Capstone: Azure OpenAI / AWS Bedrock deployment; content filters, prompt injection defense, data privacy, rate limiting — Capstone: Deploy a RAG chatbot with LangChain + Azure OpenAI + vector DB + content safety
You Build

Production RAG chatbot with LangChain + Azure OpenAI — capable of answering from custom documents, with content safety and deployment on cloud

Azure AI · OpenAI API AI Engineer · LLM Ops · Prompt Engineer
VTU: Machine Learning (Sem 6)

Production Machine Learning & MLOps

5 Weeks Intermediate

College teaches ML in Jupyter notebooks. Industry runs ML in production. Learn to build, containerize, deploy, monitor, and retrain ML models — the MLOps skills that separate hobbyists from hired professionals.

  • Week 1 — ML Pipeline Structuring: Move beyond notebooks — project structure, data versioning (DVC), experiment tracking (MLflow), reproducible pipelines — Lab: Set up a structured ML project with versioning and experiment tracking
  • Week 2 — Model Serving & APIs: Turn models into REST APIs with FastAPI; input validation, batching, async; Docker containerization for ML — Lab: Containerize a trained model as a FastAPI endpoint
  • Week 3 — Model Deployment on Cloud: Deploy containerized model on Azure AKS / AWS ECS; serverless inference with Azure Functions / AWS Lambda; API Gateway, auto-scaling — Lab: Deploy ML model to production with auto-scaling endpoint
  • Week 4 — Monitoring, Drift & Retraining: Model monitoring — prediction logging, data drift detection, concept drift; ELK stack for ML logs; automated retraining pipelines — Lab: Set up model monitoring dashboard and drift alerts
  • Week 5 — CI/CD for ML & Capstone: ML pipeline CI/CD — data validation, model training, evaluation, deployment gates; A/B testing strategies — Capstone: Deploy production ML system with CI/CD pipeline, monitoring, and auto-retraining
You Build

End-to-end production ML system: structured pipeline → containerized API → cloud deployment → monitoring → auto-retraining. Interview-ready MLOps portfolio piece

Azure ML · MLflow · FastAPI ML Engineer · MLOps · Data Scientist
VTU: Cybersecurity (Sem 7-8) · Elective

Cloud Security & SOC Operations

5 Weeks Intermediate

Cybersecurity isn't just theory — it's WAF rules, SIEM dashboards, incident response runbooks, and compliance audits. Built from real SOC experience, this course gives you the hands-on security skills that are in highest demand and shortest supply.

  • Week 1 — Cloud Security Foundations: Shared responsibility model; IAM policies, least privilege, access reviews; encryption at rest/in transit, KMS, secrets management — Lab: Audit and harden IAM policies for a multi-account AWS/Azure setup
  • Week 2 — Network Security & WAF: Security groups vs NACLs deep dive; Web Application Firewall — rules, rate limiting, geo-blocking; DDoS protection (AWS Shield, Azure DDoS) — Lab: Deploy WAF in front of a web app with custom rule set
  • Week 3 — SIEM & Log Management: ELK stack for security — ingesting cloud logs (CloudTrail, Azure Activity Log), parsing, correlation rules; building security dashboards — Lab: Set up ELK-based SIEM with cloud log ingestion and alert rules
  • Week 4 — Incident Response & Compliance: Incident response lifecycle — detection, containment, eradication, recovery; runbook creation; compliance frameworks (SOC 2, ISO 27001) — Lab: Build an incident response runbook and simulate a security incident
  • Week 5 — Secure Architecture & Capstone: Secure VPC design, network segmentation, zero-trust principles, security benchmarks (CIS) — Capstone: Design and deploy a secure cloud architecture with WAF, SIEM monitoring, IR runbook, and compliance checklist
You Build

Full cloud security stack: hardened cloud infra + WAF + SIEM (ELK) + incident response runbook + compliance audit report — SOC analyst portfolio piece

SOC 2 · ISO 27001 · CIS SOC Analyst · Cloud Security · Compliance
VTU: DBMS (Sem 4) · Web Technology (Sem 5)

Modern Backend & Database Engineering

4 Weeks Beginner-Friendly

DBMS in college teaches you SQL queries. Real backend engineering is REST APIs, connection pooling, query optimization, NoSQL, Redis caching, and cloud databases. This course bridges that gap — you'll build a production-grade backend from scratch.

  • Week 1 — Advanced SQL & Query Optimization: JOINs, subqueries, CTEs, window functions; indexing (B-tree, hash, composite), EXPLAIN ANALYZE, slow query logs; connection pooling — Lab: Optimize slow queries and design index strategy for a sample e-commerce database
  • Week 2 — REST API Development: Node.js/Express or FastAPI; CRUD endpoints, input validation, error handling, middleware, authentication (JWT); API documentation (Swagger/OpenAPI) — Lab: Build a REST API with auth, validation, and auto-generated docs
  • Week 3 — NoSQL, Caching & Message Queues: MongoDB / Cosmos DB — document modeling, indexing, aggregation; Redis — caching strategies, session store, rate limiting; message queues (RabbitMQ basics) — Lab: Integrate Redis caching and MongoDB into the API backend
  • Week 4 — Cloud Databases & Capstone: Deploy PostgreSQL on Azure/AWS, configure backups, read replicas, point-in-time recovery; database security — encryption, IAM, audit logging — Capstone: Build and deploy a full backend with SQL + NoSQL + Redis caching + cloud database + API docs
You Build

Production-grade REST API backend with SQL database, Redis caching, NoSQL store, cloud deployment, and API documentation — full-stack intern portfolio piece

MongoDB · Redis · PostgreSQL Backend Engineer · Full-Stack · API Developer
How We Train

Training Methodology

Heavy focus on practical implementation — every concept is applied in real cloud environments, not slides.

Live Demonstrations

Instructor-led real-time walkthroughs of every concept

Cloud Sandbox Labs

Practice on live Azure and AWS environments

Guided Projects

Build real-world infrastructure step by step

Real Troubleshooting

Debug live issues just like in production jobs

Hands-on Assignments

Weekly practical tasks to reinforce learning

Interactive Workshops

Collaborative problem-solving sessions

Recorded Sessions

Access all sessions anytime via LMS

Certification Prep

Exam-ready guidance for AZ-900 & AWS CCP

Delivery Model

Phase 1 — Hybrid Training Model

Flexibility and scalability through a blended approach of offline classroom sessions and online learning.

Offline Classroom

  • Instructor-led classes at our Bangalore centre
  • Hands-on lab sessions with live cloud environments
  • Interactive workshops & group problem-solving
  • College campus seminars & workshops
  • Direct mentorship & doubt clearing

Online Learning

  • Live online classes via video conferencing
  • Recorded session access (LMS)
  • Digital assignments & auto-graded quizzes
  • Remote 1:1 mentoring sessions
  • 24/7 LMS access with learning materials
Execution Roadmap

Phase-Wise Execution Plan

A structured 12-month journey from foundation to scale, designed for sustainable growth and maximum impact.

01

Foundation

Months 0–3
  • Finalize branding & identity
  • Build complete curriculum & content
  • Setup classroom & infrastructure
  • Launch social media presence
  • Conduct free introductory workshops
  • Enroll first student batch
02

Validation & Expansion

Months 3–6
  • Train initial batches with quality focus
  • Collect testimonials & case studies
  • Build college relationships
  • Expand course catalog
  • Launch recorded content library
03

Scaling

Months 6–12
  • Add advanced & specialized courses
  • Expand online presence nationally
  • Build placement & recruitment partnerships
  • Launch internship programs
  • Scale college collaborations across Karnataka
  • Build regional brand recognition
Why We Stand Out

Competitive Advantage

Unlike your college lab or typical coaching centers, we deliver enterprise-grade training that makes you actually hireable — with real projects, live cloud, and industry mentors.

Industry-Oriented Learning

Curriculum designed by professionals who have built real enterprise systems — not academicians without industry exposure

Real Enterprise Exposure

Learn on production-grade scenarios — troubleshooting, deployment, monitoring, and security that mirror real jobs

Cloud Lab Environments

Every student gets access to live Azure and AWS sandboxes for hands-on practice — not simulators

Modern AI Integration

AI woven into the curriculum — LLMs, Copilot, and automation tools in real workflows

Hands-on Troubleshooting

Debug real infrastructure issues — broken deployments, configuration errors, performance problems

Updated & Market-Aligned

Curriculum evolves with industry trends — updated quarterly based on hiring patterns and technology shifts

Business Model

Revenue Streams

A diversified multi-channel revenue model ensuring sustainability and growth.

Student Training

  • Full certification courses
  • Weekend batches
  • Crash courses
  • Internship programs

College Partnerships

  • Campus workshops & seminars
  • Faculty training programs
  • Certification bootcamps
  • Industry-aligned lab delivery

Corporate Training

  • Cloud fundamentals programs
  • AI productivity workshops
  • Infrastructure upskilling
  • Security awareness training

Future Expansion

  • Online courses & LMS platform
  • Recorded training library
  • Subscription-based learning
  • Remote mentorship programs

Investment & Partnership Opportunity

Join us in building a sustainable, scalable education business with strong long-term growth potential in India's fastest-growing tech education market.

Financial Investment Infrastructure Support Strategic Partnerships College Network Introductions Marketing Collaboration Technology Sponsorships

Together, we can transform technical education and build the next generation of cloud & AI professionals.

Long-Term Vision

Where We're Going

A recognized Cloud & AI Academy transforming technical education across India.

500+

Students trained annually

50+

College partnerships

National

Online programs across India

Placement

Network & internship ecosystem

Get in Touch

Ready to Land Your Dream Internship?

Students: Start your journey to job-ready skills. Colleges: Partner with us. Just reach out.

Contact InspireIT Edu

Whether you're a student hungry for real skills & internships, a college wanting better placement outcomes, or a professional seeking cloud/AI upskilling — let's talk.

Sultan Saad

Founder — Cloud Infrastructure & Technology Consultant

Location

Bangalore, Karnataka, India

Email

contact@inspireit.edu.in

Free Seminar

Book a free introductory workshop for your college