MLOps Training Course | MLOps Training in Ameerpet
                     Introduction to MLOps and Modern 
Machine Learning Practices
From experiments to reliable, production-ready machine learning
What you will learn
• MLOps basics and why it matters
• Workflow, components, and tools
• Use cases, challenges, and careers
• Trends shaping the future of ML
www.visualpath.in +91 7032290456
Introduction
• MLOps applies DevOps principles to machine learning systems 02
• Most ML models never reach real production use Why MLOps 
• Notebooks alone cannot deliver reliable, repeatable results matters
• Teams need automation, monitoring, and clear ownership
• Good MLOps turns experiments into dependable business value
www.visualpath.in +91 7032290456
Core Concepts
• MLOps: practices for building, deploying, and maintaining ML 
reliably
• 03Combines machine learning, software engineering, and data 
engineering
Definition and 
• Reproducibility: same code and data give the same result fundamentals
• Automation: pipelines replace manual, error-prone steps
• Monitoring and retraining keep models accurate over time
• Collaboration across data science, engineering, and operations 
teams
www.visualpath.in +91 7032290456
Key Components
• Data management: validation, versioning, and quality checks 04
• Experiment tracking: record parameters, metrics, and results
The main building 
• Model registry: store versions, stages, and approvals blocks
• CI/CD pipelines: automate testing, packaging, and release
• Model serving: expose models through APIs or batch jobs
• Monitoring: track accuracy, drift, and system health
www.visualpath.in +91 7032290456
How It Works
1. Collect data, then validate its quality 05
2. Train models and track every experiment
A simple MLOps 
3. Evaluate results and register the best model
workflow
4. Test and package the model automatically
5. Deploy to production as an API or batch job
6. Monitor performance and retrain when needed
www.visualpath.in +91 7032290456
Tools and Technologies
• Git and DVC: version control for code and data 06
• MLflow: experiment tracking and model registry
• Popular tools and Docker and Kubernetes: package and run models at scale
their purpose
• GitHub Actions and Jenkins: automate CI/CD pipelines
• Airflow and Kubeflow: orchestrate data and training workflows
• Evidently, Prometheus, Grafana: monitor drift and system health
www.visualpath.in +91 7032290456
Real-World Use Cases
• Banking: fraud detection models updated as patterns change
• Retail: demand forecasting and personalized recommendations 07
• Healthcare: medical image analysis with strict version control
How industries 
• Telecom: churn prediction using continuously refreshed customer apply MLOps
data
• Manufacturing: predictive maintenance from live sensor data
• Streaming: recommendation engines retrained and tested 
regularly
www.visualpath.in +91 7032290456
Benefits and Challenges
• Benefit: faster, more reliable model deployment 08
• Benefit: reproducible results and clear audit trails
• Benefit: better teamwork and lower operational risk What teams gain 
and face
• Challenge: model drift reduces accuracy over time
• Challenge: tool complexity and skill gaps in teams
• Challenge: managing cost, governance, and data privacy
www.visualpath.in +91 7032290456
Career Opportunities and Future Trends
• Roles: MLOps Engineer, ML Engineer, Data Engineer, Platform 
Engineer 09
• Skills: Python, Docker, Kubernetes, CI/CD, and cloud platforms
Roles, skills, 
• Also useful: SQL, Linux, ML basics, and monitoring
demand, and 
• Demand: growing as companies move AI into production outlook
• Trends: LLMOps, generative AI deployment, and model governance
• Future: more automation, feature stores, and responsible AI
www.visualpath.in +91 7032290456
Summary and Conclusion
• MLOps bridges the gap between experiments and production 10
• Automation, versioning, and monitoring are its core pillars
• Key takeawaysStart small: track experiments, then automate pipelines
• Choose tools that match your team size and needs
• MLOps skills open valuable and growing career paths
• Continuous learning keeps pace with fast-changing AI practices
www.visualpath.in +91 7032290456
For More Information About
MLOps Course
Contact Us
Address:- Flat no: 205, 2nd Floor,
   Nilagiri Block, Aditya Enclave,  Ameerpet, Hyderabad-16
   Ph. No: +91-7032290546
  www.visualpath.in
    [email protected]
www.visualpath.in +91 7032290456
THANK YOU !
For More 
Info
www.visualpath.in +91 7032290456