AWS AI Data Engineer Zero to Hero – Live Program

12 Live, Step-by-Step, Guided, Industry-Level Projects

(Zoom-Based Live Sessions – Unmute Anytime to Ask Questions)

 

Who This Is For

Ideal for professionals aiming for roles like DevOps Engineer, Cloud Engineer, Platform Engineer, SRE, AI Engineer, or Cloud Architect.

These are not YouTube-style mini-projects – every session is built on real-world, enterprise-grade use cases, simplified for better understanding.

 

Program Highlights

1. 12 Real, Industry Projects – Based on actual corporate implementations.
2. Weekly Doubt Sessions and Dedicated WhatsApp Support.
3. Help When You’re Stuck – Get personal assistance for debugging or setup issues.
4. Small Group (~25 Learners) for maximum attention and mentorship focus.
5. Lifetime Access to presentations, source code, and recordings.
6. Join Anytime – Each session covers a new project in a cyclic schedule.
7. Dedicates sessions on roadmap, how to use these projects in resume and interviews preparation.
8. Suitable for AWS, Azure, GCP all cloud aspirants. These are concepts not tied to cloud provider.

 

Batch Format

Each project is taught as a live, independent session – so you can join anytime and catch up cyclically.

Program Duration: 3 months

Mode: Live on Zoom – fully interactive with screen sharing and Q&A.

Schedule

Project Sessions

1. Every Saturday, 5:00 PM – 8:00 PM IST (~3 Hours)
2. Deep dive into each project with live coding, architecture walkthroughs, and hands-on implementation.

Doubt-Clearing Sessions

1. Every Friday, 5:00 PM – 6:30 PM IST (~1.5 Hours)
2. Live debugging, concept clarification, and issue resolution.

Fees cover the entire program, including all materials, recordings, and continuous support.

DevOps, Cloud & GenAI Industry Projects (Job-Ready Series)

Project 1: DevOps Kickstart – Agile Workflow & Team Collaboration

Tech Stack: GitHub, Jira, Agile, CI/CD Concepts

 Learn how real DevOps teams work:

1. Sprint planning & Jira workflows
2. Git branching strategy (GitFlow)
3. PR reviews, code ownership
4. CI/CD mindset & DevOps culture
5. Day to Day activities of DevOps Cloud roles

 Outcome: Clear understanding of real-world DevOps workflows and team collaboration

Project 2: AI for DevOps – GitHub Copilot & AI-Assisted Automation

Tech Stack: GitHub Copilot, AI DevOps Tools

 Use AI like real DevOps Cloud engineers use:

1. Copilot for Terraform, Docker, K8s
2. AI-assisted debugging
3. Productivity automation
4. Learn how DevOps Cloud engineers are using AI
5. Setup workstation of AI assisted DevOps Cloud engineer
6. No coding experience? This project solves how you can use AI to work same level as experienced developer. This is obviously NOT ChatGPT.

 Outcome: Modern AI-powered DevOps workflow

Project 3: Dockerized Microservices – Production-Ready Containers

Tech Stack: Docker, Dockerfile (Multi-stage), Docker Compose

 Build & optimize containers:

1. Multi-stage Docker builds
2. Image size optimization
3. Secure Dockerfiles
4. Multi-service app with Docker Compose

 Outcome: Industry-level containerization skills

Project 4: Enterprise CI/CD Pipelines with GitHub Actions

Tech Stack: GitHub Actions, Docker, Self-hosted Runners

 Build real CI/CD pipelines:

1. Build, test, scan, deploy pipelines
2. Self-hosted runners (real enterprise setup)
3. Secrets & environment protection

 Outcome: Hands-on CI/CD experience used in companies

Project 5: Terraform Project 1 – Infrastructure as Code Foundations

Tech Stack: Terraform, AWS, Remote State (S3), Locking

 Provision infrastructure using Terraform:

1. Modular Terraform design
2. Remote state & state locking
3. Environment separation (dev / stage / prod)

 Outcome: Strong Terraform foundation with real infra

Project 6: Terraform Project 2 – CI/CD Resilient Infrastructure

Tech Stack: Terraform, GitHub Actions, Docker

 Solve real Terraform challenges:

1. Terraform in CI/CD
2. Rollback-safe deployments
3. Drift detection & recovery

 Outcome: Production-grade Terraform pipelines

Project 7: Golden AMI Pipeline with Packer & Terraform

Tech Stack: Packer, Terraform, EC2

 Create hardened images:

1. Golden AMI creation
2. Security hardening
3. Canary deployment strategy

 Outcome: Enterprise image automation skills

Project 8: Managing 100+ Servers Using Ansible

Tech Stack: Ansible, Dynamic Inventory, SSH Hardening

 Automate at scale:

1. Ansible roles & playbooks
2. Dynamic inventory (AWS)
3. Security & compliance automation

 Outcome: Mass infrastructure automation expertise

Project 9: Kubernetes Production Cluster Deployment

Tech Stack: Kubernetes, EKS, Helm, Ingress

 Deploy microservices on Kubernetes:

1. Helm-based deployments
2. Ingress, services, autoscaling
3. Secure and scalable K8s architecture

 Outcome: Real Kubernetes project experience

Project 10: GitOps with Argo CD (Dedicated Project)

Tech Stack: Argo CD, GitHub, Kubernetes, Helm

 Implement GitOps:

1. Declarative deployments
2. Sync strategies
3. Blue-green & canary releases

 Outcome: True GitOps deployment mastery

Project 11: Monitoring & Observability Stack

Tech Stack: Prometheus, Grafana, CloudWatch, Helm

 End-to-end observability:

1. Metrics, dashboards & alerts
2. SLOs / SLAs
3. Deployment monitoring

 Outcome: Production monitoring skills

Project 12: GenAI Application ,LLM agent, MLOps

Tech Stack: Amazon Bedrock, LangChain, API Gateway

 Build real GenAI apps:

1. LLM based API
2. CI/CD for AI applications
3. MLOps