End-to-End ML Pipelines
LLMOps & GenAI
Industry Best Practices
Real Deployment Projects
Career Guidance
📚 Detailed MLOps Course Syllabus
1
Module 1: ML Fundamentals Recap
2 weeks
- ML Pipeline Overview
- Model Training Basics
- Data Preprocessing
- Feature Engineering
- Model Evaluation
2
Module 2: Experiment Tracking
2 weeks
3
Module 3: Data Pipelines
2 weeks
4
Module 4: Model Deployment
3 weeks
5
Module 5: Kubernetes for ML
2 weeks
6
Module 6: Monitoring & LLMOps
3 weeks
7
Module 7: Capstone Project
2 weeks
Career Opportunities
- MLOps Engineer
- ML Engineer
- Data Engineer
- AI Infrastructure Engineer
- Platform Engineer
Salary: ₹8-28 LPA
Tools & Technologies
MLflow
Kubeflow
Docker
Kubernetes
Airflow
Certification
MLOps Professional Certificate
📋 Prerequisites for MLOps Course
Python programming
ML basics
Docker knowledge helpful
