AI Mentor
DR. LOVLEEN GAUR
What You’ll Learn
A hands-on journey from Docker basics to building production-ready MLOps pipelines—designed by NanoSchool’s Deep Science Learning Organisation under NSTC guidelines.
Docker Fundamentals
Build, run, and manage lightweight containers.
Kubernetes Orchestration
Deploy and scale containerized applications.
MLOps Pipelines
Automate AI model training, testing, and deployment.
Production Deployment
Full-stack workflow: from model to scalable cloud service.
Who Should Enroll?
Ideal for DevOps engineers, MLOps engineers, and professionals across India—especially in Delhi NCR—looking to deploy AI models at scale.
- Engineers with basic DevOps and Python knowledge
- Developers seeking to specialize in MLOps
- Students pursuing production engineering roles
- AI practitioners needing deployment skills
Hands-On Projects
Dockerise an AI Model
Package a Python-based ML model into a Docker container.
Kubernetes Deployment
Deploy the containerized model on a local K8s cluster.
Capstone
End-to-End MLOps Pipeline
Build a CI/CD pipeline deploying models on K8s, reviewed by NSTC mentors.
4-Week Syllabus
Total: ~40 hours • Lifetime LMS access • Delhi NCR support
Week 1: Docker Fundamentals
- Containers vs VMs, Docker architecture
- Dockerfile, images, containers
- Lab: Containerise a simple Python script
Week 2: Advanced Docker
- Multi-stage builds, networking, volumes
- Managing container lifecycles
- Lab: Containerise a full AI model
Week 3: Kubernetes Basics
- K8s architecture, pods, deployments
- Services, load balancing, scaling
- Lab: Deploy the AI model on K8s
Week 4: MLOps & CI/CD Pipelines
- GitOps, ArgoCD, MLflow
- Automated testing & deployment
- Capstone: Full MLOps pipeline with K8s
NanoSchool LMS & NSTC Mentorship
Access our browser-based LMS with lifetime access. Get support from mentors certified by the NanoSchool Technology Council (NSTC).
NSTC-Accredited Certificate
Verified by the NanoSchool Technology Council (NSTC). Shareable on LinkedIn. Recognized by Indian employers and startups in Delhi NCR.
Frequently Asked Questions
What are the prerequisites for this course?
You should have a good understanding of basic DevOps concepts (like version control, CI/CD) and Python programming. Familiarity with cloud platforms is helpful.
Will I work with real cloud platforms?
Yes, the course includes hands-on labs using local tools like Docker Desktop and Minikube, with guidance on deploying to cloud providers like AWS, GCP, or Azure.
How does this fit into the AI development lifecycle?
This course focuses on the ‘Production’ phase. You’ll learn how to take a trained AI model and deploy it reliably and scalably in a production environment using Docker and Kubernetes.
