Coursera

Master Agentic AI: Core Principles & Real-World PC Professional Certificate

Coursera

Master Agentic AI: Core Principles & Real-World PC Professional Certificate

Build and Operate Autonomous Agent Systems.

Learn agent design, MLOps, and security governance with hands-on projects for ML/AI practitioners.

Access provided by Interbank

Earn a career credential that demonstrates your expertise
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Earn a career credential that demonstrates your expertise
Intermediate level

Recommended experience

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

What you'll learn

  • Design modular agent architectures and translate goals into reward signals for aligned behavior.

  • Build CI/CD and retraining pipelines that detect drift and promote vetted models to production.

  • Create reproducible telemetry pipelines, dashboards, and analytics to monitor agent performance.

  • Apply threat modeling and dependency analysis to secure agentic systems and document mitigations.

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English
Recently updated!

March 2026

See how employees at top companies are mastering in-demand skills

 logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Advance your career with in-demand skills

  • Receive professional-level training from Coursera
  • Demonstrate your technical proficiency
  • Earn an employer-recognized certificate from Coursera

Professional Certificate - 4 course series

Building and Optimizing AI Agent Workflows

Building and Optimizing AI Agent Workflows

Course 1, 17 hours

What you'll learn

  • Design ethical RL reward functions that align agent behavior and analyze AI's legal and societal implications.

  • Build modular, scalable agent systems with clear APIs using advanced reasoning-loop architectures like ReAct.

  • Apply search algorithms & Big-O analysis to optimize pipelines, balancing performance, cost, and success rates.

  • Build reusable ML pipelines to transform data and apply interpretability techniques to detect model bias.

Skills you'll gain

Category: Responsible AI
Category: Feature Engineering
Category: Generative AI
Category: System Design and Implementation
Category: Agentic Workflows
Category: Agentic systems
Category: Python Programming
Category: Model Evaluation
Category: Data Ethics
Category: Model Optimization
Category: Data Transformation
Category: Generative AI Agents
Category: Fine-tuning
Category: Code Reusability
Category: Model Training
Category: Reinforcement Learning
Category: Artificial Intelligence
Category: MLOps (Machine Learning Operations)
Category: AI Orchestration
Category: Model Deployment
Validating and Safeguarding Production AI

Validating and Safeguarding Production AI

Course 2, 17 hours

What you'll learn

  • Build automated CI/CD pipelines to retrain and redeploy models, triggered by drift detection analysis.

  • Write clean, performant Python by applying profiling, testing, and dependency management best practices.

  • Implement anomaly detection using statistical methods and create a human feedback loop to label data and retrain models.

  • Create unbiased datasets, evaluate hyperparameters, and analyze model performance to recommend a production model.

Skills you'll gain

Category: MLOps (Machine Learning Operations)
Category: CI/CD
Category: Continuous Monitoring
Category: Maintainability
Category: Data Validation
Category: Software Engineering
Category: Anomaly Detection
Category: Performance Tuning
Category: Model Deployment
Category: Security Testing
Category: Model Evaluation
Category: Secure Coding
Category: Python Programming
Category: DevOps
Category: Software Quality Assurance
Category: Integration Testing
Category: Model Training
Category: Sampling (Statistics)
Category: Performance Testing
Category: AI Security
Analyzing and Securing AI System Performance

Analyzing and Securing AI System Performance

Course 3, 16 hours

What you'll learn

  • Use data aggregation and A/B testing to analyze metrics, create clear visualizations, and build automated KPI alerts.

  • Clean raw data, evaluate quality trade-offs, and create reproducible, versioned notebooks for peer replication.

  • Secure APIs using OWASP guidelines, analyze vulnerability scans, and evaluate secret management solutions.

  • Create structured threat models to analyze, document, and prioritize system security risks and vulnerabilities.

Skills you'll gain

Category: A/B Testing
Category: Application Security
Category: AI Security
Category: Analytics
Category: Open Web Application Security Project (OWASP)
Category: Threat Modeling
Category: Cyber Governance
Category: Data Presentation
Category: System Monitoring
Category: Interactive Data Visualization
Category: MLOps (Machine Learning Operations)
Category: Vulnerability Assessments
Category: Data Visualization
Category: Data Management
Category: Responsible AI
Category: Data Governance
Category: Application Programming Interface (API)
Category: Secure Coding
Category: Data Processing
Category: Threat Management

What you'll learn

  • Develop portfolio artifacts (e.g., project write-up, reproducibility README, demo script) to showcase agent design and governance work.

  • Compose a role-specific resume and LinkedIn summary that articulates expertise in systems, MLOps, and security governance.

  • Design a 5–7-minute technical presentation to explain problem framing, design decisions, evaluation, and mitigation strategies.

Skills you'll gain

Category: Communication Strategies
Category: MLOps (Machine Learning Operations)
Category: Technical Documentation
Category: AI Security
Category: Agentic systems
Category: GitHub
Category: Coaching
Category: Technical Writing
Category: Problem Solving
Category: Project Documentation
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Professional Development
Category: Technical Communication
Category: Agentic Workflows
Category: Portfolio Management
Category: Generative AI Agents

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Professionals from the Industry
451 Courses67,838 learners

Offered by

Coursera

Why people choose Coursera for their career

Felipe M.

Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

¹Career improvement (i.e. promotion, raise) based on Coursera learner outcome survey responses, United States, 2021.