Coursera

Master Agentic AI: Core Principles & Real-World PC 专业证书

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Coursera

Master Agentic AI: Core Principles & Real-World PC 专业证书

Build and Operate Autonomous Agent Systems.

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

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推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
获得职业证书,展示您的专业知识
中级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • 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.

要了解的详细信息

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授课语言:英语(English)
最近已更新!

March 2026

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专业认证 - 4门课程系列

Building and Optimizing AI Agent Workflows

Building and Optimizing AI Agent Workflows

第 1 门课程, 小时

您将学到什么

  • 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.

您将获得的技能

类别:Responsible AI
类别:Process Optimization
类别:Generative AI
类别:Feature Engineering
类别:System Design and Implementation
类别:Business Ethics
类别:Model Deployment
类别:Data Transformation
类别:Agentic Workflows
类别:API Design
类别:Performance Tuning
类别:Reinforcement Learning
类别:Software Architecture
类别:Algorithms
类别:Model Evaluation
类别:Python Programming
类别:MLOps (Machine Learning Operations)
类别:Data Ethics
类别:Agentic systems
类别:Artificial Intelligence
Validating and Safeguarding Production AI

Validating and Safeguarding Production AI

第 2 门课程, 小时

您将学到什么

  • 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.

您将获得的技能

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

Analyzing and Securing AI System Performance

第 3 门课程, 小时

您将学到什么

  • 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.

您将获得的技能

类别:AI Security
类别:Analytics
类别:Threat Modeling
类别:Data Management
类别:Jupyter
类别:Data Processing
类别:MLOps (Machine Learning Operations)
类别:System Monitoring
类别:Data Cleansing
类别:Secure Coding
类别:API Gateway
类别:DevSecOps
类别:Data Governance
类别:Cyber Governance
类别:Data Quality
类别:Open Web Application Security Project (OWASP)
类别:A/B Testing
类别:Data Visualization
类别:Application Security
类别:Data Validation
Portfolio and Industry Readiness for Agentic AI Architects

Portfolio and Industry Readiness for Agentic AI Architects

第 4 门课程, 小时

您将学到什么

  • 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.

您将获得的技能

类别:MLOps (Machine Learning Operations)
类别:Communication Strategies
类别:Agentic systems
类别:Verbal Communication Skills
类别:Data Presentation
类别:Artificial Intelligence and Machine Learning (AI/ML)
类别:GitHub
类别:AI Orchestration
类别:Professional Development
类别:Coaching
类别:Project Documentation
类别:Agentic Workflows
类别:Technical Documentation
类别:Technical Writing
类别:Technical Communication
类别:Portfolio Management
类别:AI Security

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人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

自 2018开始学习的学生
''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情,我就可以学习。'

Jennifer J.

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''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.

自 2021开始学习的学生
''如果我的大学不提供我需要的主题课程,Coursera 便是最好的去处之一。'

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''学习不仅仅是在工作中做的更好:它远不止于此。Coursera 让我无限制地学习。'
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常见问题

¹ 基于美国 2021 年 Cousera 学生结果调查的结果。