Coursera

Agentic AI Performance & Reliability Specialization

Coursera

Agentic AI Performance & Reliability Specialization

Build Reliable Production AI Systems.

Deploy, monitor, and optimize AI models with automated pipelines and real-time performance tracking.

LearningMate

Instructor: LearningMate

Access provided by AUB

Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Build automated MLOps pipelines for deploying, monitoring, and retraining AI models in production environments

  • Implement real-time anomaly detection and performance monitoring systems with KPI dashboards and automated alerts.

  • Design feedback loops and reproducible workflows to ensure AI reliability and continuous improvement at scale.

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Taught in English
Recently updated!

December 2025

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Specialization - 8 course series

Partition & Monitor AI Models Effectively

Partition & Monitor AI Models Effectively

Course 1, 2 hours

What you'll learn

  • Partition data fairly, monitor models for drift using PSI/KL divergence, and build automated retraining pipelines for reliable, production-grade AI.

Automate, Evaluate and Deploy ML Models Confidently

Automate, Evaluate and Deploy ML Models Confidently

Course 2, 3 hours

What you'll learn

  • Evaluate model optimization trials, build automated CI/CD pipelines, and confidently deploy production-ready machine learning models.

Detect AI Anomalies: Real-Time Outliers

Detect AI Anomalies: Real-Time Outliers

Course 3, 3 hours

What you'll learn

  • Implement real-time anomaly detection to find critical outliers and differentiate true system failures from benign data drift in AI systems.

Automate, Analyze, and AI Feedback

Automate, Analyze, and AI Feedback

Course 4, 3 hours

What you'll learn

  • Design automated feedback loops to capture human insights, analyze model performance, and retrain AI to meet specific operational goals.

Analyze Agent Performance: Build and Test

Analyze Agent Performance: Build and Test

Course 5, 2 hours

What you'll learn

  • Aggregate agent performance data and apply statistical A/B tests to objectively measure and validate improvements in AI systems.

Visualize and Alert AI Performance KPIs

Visualize and Alert AI Performance KPIs

Course 6, 2 hours

What you'll learn

  • Design dashboards and automated alerts, translating complex AI performance data into clear, actionable insights for stakeholders.

Clean, Analyze, and Visualize Your Data

Clean, Analyze, and Visualize Your Data

Course 7, 2 hours

What you'll learn

  • Develop core data preparation and exploration skills for AI. Implement data validation and visualization to ensure high-quality data for models.

Evaluate and Reproduce Data Findings Fast

Evaluate and Reproduce Data Findings Fast

Course 8, 3 hours

What you'll learn

  • Learners will apply statistical analysis for sampling and build reproducible data workflows using parameterization and data versioning.

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Instructor

LearningMate
275 Courses23,530 learners

Offered by

Coursera

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