Techpratham's MLOps training gives students the tools they need to manage, automate, and improve the ML lifecycle. You'll learn a lot about CI/CD pipelines, model versioning, monitoring, and deployment strategies. The course also talks about containerization, cloud integration, and managing models in real time. By the end, you'll know how to make machine learning systems for businesses that can grow and are reliable.
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MLOps
With Techpratham, you can learn how to use MLOps to make the machine learning lifecycle easier, from building models to deploying them in production. Learn how to automate, keep an eye on, and grow AI workflows.
5/5(4,890 Reviews)
Level
Advanced
Duration
8 weeks
Placement Client
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About MLOps
Training Plan
01
About trainer
Working professional who is carrying more then 10 years of industry experience.
02
Decks & Updated Content
Access to updated presentation decks shared during live training sessions.
03
e-Book
E-book provided by TechPratham. All rights reserved.
04
Assignments & MCQs
Module-wise assignments and MCQs provided for practice.
05
Video Recording
Daily Session would be recorded and shared to the candidate.
06
Projects
Live projects will be provided for hands-on practice.
07
Resume Building
Expert-guided resume building with industry-focused content support.
08
Interview Preparation
Comprehensive interview preparation with real-time scenario practice.
<h1><strong>MLOps</strong></h1> Course Curriculum
Introduction to MLOps
Understand the fundamentals and importance of MLOps.
What is MLOps?
ML Lifecycle Management
DevOps vs MLOps
Benefits for Businesses
Real-World Use Cases
Machine Learning Lifecycle Management
Learn about different stages of an ML project including data collection, preprocessing, model building, deployment, and monitoring.
Data Preparation
Model Training
Model Evaluation
Production Deployment
Version Control & Experiment Tracking
Explore versioning strategies for datasets, models, and experiments to ensure reproducibility and transparency in ML projects.
Git & GitHub
DVC (Data Version Control)
MLflow Tracking
Experiment Logging
Continuous Integration & Continuous Deployment (CI/CD)
Implement CI/CD pipelines for machine learning models to automate testing, integration, and deployment processes.
Jenkins / GitHub Actions
Automated Testing
Deployment Pipelines
Model Registry
Containerization & Orchestration
Understand the role of Docker and Kubernetes in packaging ML models and managing scalable deployments in cloud environments.
Docker Basics
Kubernetes Pods & Services
Helm Charts
Cloud Deployment
Model Serving & APIs
Learn how to serve ML models as APIs for integration with applications and enable real-time or batch inference.
Flask & FastAPI
REST & gRPC APIs
Batch Inference
Real-time Predictions
Learn Ai Courses
No related courses found
Additional Program Highlights
Comprehensive study materials and resources
HD
Professional resume building session
HD
Master your interview skills
HD
Real-world project demonstrations
HD
Upcoming Batches
Can't find a batch you were looking for?
Who Should Take <h1><strong>MLOps</strong></h1>
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Working Professionals
Ops/Administrators/HR
Developers
BA/QA Engineers
Cloud / Infra
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Key Projects
<h1><strong>MLOps</strong></h1>
End-to-End ML Pipeline with CI/CD
Use CI/CD tools like GitHub Actions or Jenkins to build a full ML pipeline that automates the process of getting data, training models, testing them, and deploying them. This project makes sure that students know how to use automation workflows.
Customer Churn Prediction System
Use CI/CD tools like GitHub Actions or Jenkins to build a full ML pipeline that automates the process of getting data, training models, testing them, and deploying them. This project makes sure that students know how to use automation workflows.
Real-Time Sentiment Analysis with Monitoring
Make a sentiment analysis model that can be used through APIs and add monitoring tools to keep an eye on how well the model is working, find drifts, and retrain it automatically. This project is all about making things work reliably in production.
Placement Process
Live Class with Industry Use Cases
- Interactive learning
- Real-world examples
- Expert guidance
- Doubt resolution
Daily Assignment & Weekly Assessments
- Hands-on practice
- Concept reinforcement
- Weekly evaluation
- Timely feedback
Project Testing & Deployment
- Project development
- Testing practice
- Deployment exposure
- Portfolio creation
Interview Preparation (Mock, PD, Alumni Session)
- Mock interviews
- Personal development
- Alumni guidance
- Confidence building
Resume Building
- Resume crafting
- Industry-focused format
- Skills highlighting
- Professional presentation
Placement
- Job assistance
- Interview support
- Career guidance
- Opportunity access
Latest Hiring
No hiring posts
Recently Placed Candidates
No placements available
Latest Hiring
No hiring posts
Our Success Mantra
Commitment
- Ensuring quality training every day
Fulfillment
- Meeting learning goals with confidence
Accomplishment
- Students achieving industry-ready expertise
Our Learner Voice
Beyond Courses:
Additional Support We Provide
24/7 Support
LinkedIn Profile
Resume Writing
Alumni Sessions
Interview Preparation
Live Projects
What Makes TechPratham Training Different?
Feature
TechPratham Advantage
Industry Standard Institutes
Real-World Implementation
Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.
Restricted or simulation-based access that lacks real-world complexity.
Subject Matter Experts
Mentorship from certified professionals with 15+ years of global industry experience.
Generic instructors with no hands-on implementation background.
2026 Ready Curriculum
AI-driven curriculum with advanced platform integrations and real-world configurations.
Basic, outdated syllabus that misses key technical integrations.
Daily & Weekly assignments
Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.
Self-paced learning with no accountability or progress tracking.
End-to-End Lifecycle
Hands-on project testing and deployment with portfolio-ready real-world exposure.
Basic lab exercises without any deployment or testing practice.
Interview Readiness
Structured interview preparation including mock interviews, PD sessions, and alumni guidance.
Minimal support limited to a generic certificate of completion.
Placement Support
Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.
Basic career tips with no direct industry connections.
Training Support
24/7 technical doubt resolution and personalized mentoring support.
Limited mentor availability and no support after class hours.
Affordable Fees
Competitive fixed pricing with flexible payment options and transparent fee structure.
Inflated fees with hidden costs and low return on investment.
Real-World Implementation
Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.
Restricted or simulation-based access that lacks real-world complexity.
Subject Matter Experts
Mentorship from certified professionals with 15+ years of global industry experience.
Generic instructors with no hands-on implementation background.
2026 Ready Curriculum
AI-driven curriculum with advanced platform integrations and real-world configurations.
Basic, outdated syllabus that misses key technical integrations.
Daily & Weekly assignments
Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.
Self-paced learning with no accountability or progress tracking.
End-to-End Lifecycle
Hands-on project testing and deployment with portfolio-ready real-world exposure.
Basic lab exercises without any deployment or testing practice.
Interview Readiness
Structured interview preparation including mock interviews, PD sessions, and alumni guidance.
Minimal support limited to a generic certificate of completion.
Placement Support
Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.
Basic career tips with no direct industry connections.
Training Support
24/7 technical doubt resolution and personalized mentoring support.
Limited mentor availability and no support after class hours.
Affordable Fees
Competitive fixed pricing with flexible payment options and transparent fee structure.
Inflated fees with hidden costs and low return on investment.
Why is MLOps important in today’s AI industry?
What is MLOps?
Why is MLOps important?
What are the main components of MLOps?
Do I need coding skills for MLOps?
How does MLOps differ from DevOps?
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