Introduction to MLOps

SKU: M2002
4 Lesson
|
4 Hours
Introduction to MLOps explains how machine learning models move from development to production. Learn the ML lifecycle, key challenges, and core components behind real-world ML systems.
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Introduction to MLOps

Overview

Prerequisites

  • Basic understanding of Machine Learning concepts
  • Familiarity with Python programming
  • Basic knowledge of Git (recommended but not mandatory)
  • Understanding of how ML models are trained (helpful)
  • Interest in deploying ML models to production

What Will You Learn

  • What MLOps is and why it is important
  • The end-to-end Machine Learning lifecycle
  • Key challenges in deploying ML models to production
  • Core components of MLOps (versioning, CI/CD, monitoring)
  • High-level MLOps architecture and workflows
  • How modern companies manage production ML systems
  • Roadmap to becoming an MLOps Engineer

Key Features

Course Curriculum

1. Definition of MLOps
2. Why MLOps is needed
3. ML lifecycle overview
4. MLOps vs DevOps vs Data Science
1. Why ML projects fail in production
2. Data drift & model degradation
3. Reproducibility issues
4. Deployment complexity
1. Version Control
2. Experiment Tracking
3. Containerization
4. CI/CD basics
5. Monitoring basics
1. Training pipeline
2. Deployment pipeline
3. Monitoring loop
4. Continuous improvement cycle
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1-800-7430-173 (US Toll Free)
+91 7240740740 (India)
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Course Fees

Online Class Room Program

US $ 199.00
100% Money Back Guarantee
  • Duration : 4 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 28 May 2026
  • Weekday Batch 01 Jun 2026
  • Weekend Batch 30 May 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support
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