The MLOps Internship™ Build. Monitor. Automate. Deploy.

Build. Monitor. Automate. Deploy.

Stop building machine learning models that only work in notebooks. Learn how to deploy, monitor, retrain, and manage production-ready AI systems through a realistic 12-week MLOps internship simulation.

Inside this practical guide, you'll build real-world projects using MLflow, DVC, Docker, Airflow, FastAPI, Grafana, Prometheus, GitHub Actions, Feast, and Evidently AI while solving production incidents, detecting model drift, automating retraining, and deploying reliable ML systems.

What you'll get:

• 📖 12-week structured internship experience
• 💻 Hands-on coding exercises and projects
• 🚀 Production-ready MLOps workflows
• 📊 Architecture diagrams and engineering scenarios
• 📱 QR codes to GitHub notebooks and resources
• 🎓 Portfolio projects to showcase your skills

Perfect for: Computer Science students, AI/ML interns, Data Scientists, Machine Learning Engineers, MLOps Engineers, postgraduate students, and AI enthusiasts.

Format: Digital eBook (PDF) + Companion GitHub Resources

Become the engineer who doesn't just build AI models—but keeps them running in the real world.