Intermediate to Expert45 Days

AI MLOps

Machine Learning Operations Mastery

Master the complete Machine Learning Operations lifecycle from model development to production deployment. Learn industry-standard MLOps practices, automation tools, and techniques to build, deploy, monitor, and maintain ML systems at scale.

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Course Rating
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AI MLOps Course - Machine Learning Operations
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Course Overview

Our comprehensive AI MLOps course focuses specifically on Machine Learning Operations - the practice of deploying, monitoring, and maintaining ML models in production environments. You'll master the complete MLOps lifecycle, from experiment tracking to automated retraining pipelines. The course includes 26 detailed modules covering industry-standard tools, platforms, and best practices used by leading tech companies.

26
Modules
140
Total Sessions
75%
Hands-on Labs

MLOps Technology Stack

Experiment Tracking

MLflow, W&B, Neptune.ai

Model Deployment

TensorFlow Serving, TorchServe, Seldon

Pipeline Orchestration

Kubeflow, Airflow, Prefect

Monitoring

Prometheus, Grafana, Evidently

Course Key Highlights

MLOps Specialists

Learn from certified MLOps engineers and data scientists

Career Advancement

100% placement support for MLOps engineer roles

Production Systems

Build enterprise-grade ML systems and pipelines

Industry Tools

Master cutting-edge MLOps platforms and frameworks

Great Value

Specialized MLOps training at competitive pricing

Flexible Timing

Multiple batch options to fit your schedule

Easy Financing

Zero-cost EMI options for easy enrollment

Specialized Focus

Deep dive into MLOps without dilution

Complete AI MLOps Syllabus

Comprehensive 26-module curriculum covering machine learning operations from fundamentals to advanced. Master MLOps engineering, automation, and production ML systems with industry best practices.

1

Introduction to MLOps and AI Operations

Duration: 1 Week

Topics Covered:

Understanding Machine Learning Operations (MLOps) fundamentals
MLOps vs DevOps: similarities, differences, and integration points
ML lifecycle management and operational challenges
Industry standards and MLOps maturity models
MLOps culture and organizational transformation
Business value and ROI of MLOps implementation
MLOps team structure and role definitions
Common MLOps challenges and solutions
MLOps market landscape and tool ecosystem
Future trends in ML operations and automation
Course ProgressModule 1 of 26
26
Modules
75
Days Duration
190
Total Sessions
15+
Live Projects

Frequently Asked Questions

Course Features

LevelIntermediate/Expert
Class TypeVirtual & Hybrid
Duration45 Days
Lectures65
Labs/Projects75
Total Sessions140
CertificateYes
Daily Test1 daily Test
Weekly Test1 weekly Test
Mock Test6 mock Test

Additional Benefits:

End-to-End ML Pipeline Development
Model Deployment & Serving
Advanced Monitoring & Observability
Automated ML Workflows
100% Placement Assistance
Feature Store Implementation
Model Governance & Compliance
Real-time ML Applications

Master MLOps Today!

Join our specialized 26-module MLOps program and become an expert in Machine Learning Operations

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