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Automating Decision Workflows with AI

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Automating Decision Workflows with AI

Instructor: Edureka

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

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

What you'll learn

  • Identify the key principles of automation and orchestration in AI-powered decision systems.

  • Analyze Generative and Agentic AI approaches to enhance autonomous decision-making.

  • Evaluate responsible AI frameworks to ensure fairness, transparency, and accountability in automation.

  • Develop scalable, low-code deployment strategies using MLOps and cloud technologies.

Details to know

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Assessments

14 assignments¹

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the AI-Powered Decision Intelligence Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

This course unlocks the next frontier of Decision Intelligence where AI meets automation to drive real-time, autonomous, and responsible decision-making at scale.

You’ll learn to orchestrate multi-step processes, stream real-time insights, and build automated systems that boost accuracy, speed, and business impact. You’ll dive into Generative and Agentic AI to create autonomous, insight-driven decisions supported by strong ethical frameworks that keep every outcome transparent, fair, and accountable. Finally, you’ll master deploying and scaling these systems through MLOps, cloud APIs, and low-code platforms, making enterprise-ready automation efficient, scalable, and easy to adopt. By the end of this course, you will be able to: - Identify the key functions of intelligent automation pipelines for AI-driven decision-making. - Analyze Generative and Agentic AI models to design adaptive and autonomous decision workflows. - Evaluate responsible AI frameworks to ensure ethical and accountable automation practices. - Develop deployment strategies using MLOps and cloud technologies for continuous performance. - Design low-code and no-code solutions to expand and democratize Decision Intelligence adoption. This course is ideal for AI engineers, data scientists, automation architects, and business technology leaders who want to bridge AI innovation with scalable automation. A foundation in Decision Intelligence or machine learning will enhance your learning experience. Join this course to master the integration of AI, automation, and responsibility and learn to build decision systems that think, act, and evolve with intelligence.

Uncover how intelligent decision pipelines transform data into measurable business value. This module introduces the art and science of connecting analytics to action framing business problems, designing real-time data workflows, and implementing Decision Support Systems (DSS) that enhance strategic decision-making. Through hands-on exercises and demonstrations, you’ll learn how data, automation, and analytics converge to power modern AI-driven decision ecosystems.

What's included

14 videos8 readings4 assignments

14 videos•Total 81 minutes
  • Specialization Introduction•6 minutes
  • Course Introduction•5 minutes
  • The Role of Automation in Modern Decision Pipelines•6 minutes
  • Orchestrating Multi-Step Decisions with AI•6 minutes
  • Measuring Efficiency and Accuracy in Automated Decisions•6 minutes
  • Demonstration: Sales Data Analyzer using Replit•6 minutes
  • Fundamentals of Real-Time Decision Intelligence•6 minutes
  • Adaptive Decision Models Using Continuous Data Streams•6 minutes
  • Building Real-Time Feedback Loops for Adaptive Systems•5 minutes
  • Applying Decision Automation Across Sectors•5 minutes
  • Building Scalable Decision Workflows for Operational Success•6 minutes
  • Demonstration: AI-powered customer query agent with Flowise•6 minutes
  • Measuring Automation ROI and Key Performance Outcomes•6 minutes
  • Demonstration: Industrial Quality Assurance through Automated Decision Workflows•6 minutes
8 readings•Total 90 minutes
  • Course Overview•15 minutes
  • AI Decision Orchestration: Combining DataOps, MLOps, and BizOps.•10 minutes
  • Intelligent Automation and Workflow Design•10 minutes
  • Code Smarter in the Cloud with Replit•10 minutes
  • Real-Time and Event-Driven Decisioning•10 minutes
  • Industry Case Studies: DI-Driven Innovation and Efficiency•10 minutes
  • Intelligent Decision Workflows for Quality Assurance in Smart Manufacturing•10 minutes
  • Module Summary: Automation and Intelligent Orchestration•15 minutes
4 assignments•Total 33 minutes
  • Knowledge Check: Automation and Intelligent Orchestration•15 minutes
  • Knowledge Check: Foundations of Intelligent Automation•6 minutes
  • Knowledge Check: Real-Time and Event-Driven Decisioning•6 minutes
  • Knowledge Check: Industry Applications of Decision Automation•6 minutes

Step into the world of next-generation AI where creativity, autonomy, and ethics converge. This module empowers you to harness Generative AI for innovation, Agentic AI for autonomous decision-making, and Ethical AI for transparency and trust. Through practical demonstrations and case studies, you’ll explore how advanced AI models create new insights, coordinate intelligent agents, and enforce responsible governance across automated decision systems.

What's included

13 videos8 readings4 assignments

13 videos•Total 75 minutes
  • Introduction to Generative AI•6 minutes
  • Core Generative AI Modeling Concepts•6 minutes
  • Key Models in Generative AI (GANs, VAEs, LLMs)•6 minutes
  • Transformers: The AI Backbone•7 minutes
  • Demonstration: Visualizing Attention in Transformer Model•6 minutes
  • Understanding Agentic AI•6 minutes
  • Designing Agents for Sequential Decision Tasks•5 minutes
  • Human-AI Collaboration in Agentic Environments•5 minutes
  • Demonstration: Enhancing Automated Workflows with Formatter and AI by Zapier•6 minutes
  • Ethical Imperatives in AI-Based Decision Systems•5 minutes
  • Implementing Bias Detection and Model Auditing Techniques•5 minutes
  • Building Ethical Oversight Mechanisms for Decision Workflows•5 minutes
  • Demonstration: Running Bias Detection and Fairness Analysis•6 minutes
8 readings•Total 85 minutes
  • Generative AI Applications in Decision Intelligence•10 minutes
  • Overview of BERT, GPT, and Hugging Face•10 minutes
  • Interpreting AI Focus: Visualizing Attention in Transformer Models•10 minutes
  • Architecture of Agentic Systems•10 minutes
  • Intelligent Workflow Design with Zapier Formatter and AI•10 minutes
  • Global AI Governance Frameworks•10 minutes
  • Ensuring Fairness in AI: Bias Detection and Mitigation Workflows•10 minutes
  • Module Summary: Generative, Agentic, and Ethical Decision Intelligence•15 minutes
4 assignments•Total 33 minutes
  • Knowledge Check: Generative, Agentic, and Ethical Decision Intelligence•15 minutes
  • Knowledge Check: Generative AI in Decision Intelligence•6 minutes
  • Knowledge Check: Agentic AI and Autonomous Decision Systems•6 minutes
  • Knowledge Check: Ethics, Bias, and Oversight in AI Decision Systems•6 minutes

Unlock the power of scalable AI deployment and enterprise-wide automation. This module focuses on bringing AI decision systems to production using MLOps, cloud platforms, and low-code environments. You’ll learn how to operationalize models, integrate APIs for performance optimization, and design intuitive low-code workflows that extend AI accessibility beyond technical teams, driving smarter, faster, and more inclusive decision-making across the organization.

What's included

13 videos9 readings4 assignments

13 videos•Total 64 minutes
  • Introduction to MLOps and the Model Lifecycle•5 minutes
  • Continuous Integration and Continuous Delivery (CI/CD) in AI Systems•5 minutes
  • Monitoring, Retraining, and Drift Detection•4 minutes
  • Demonstration: End-to-End MLOps Workflow using MLflow•6 minutes
  • Fundamentals of Cloud-Based AI Deployments•5 minutes
  • Demonstration: Setting Up Analytics for an API•5 minutes
  • Integrating APIs with Cloud-Based Decision Platforms•5 minutes
  • Scaling AI Workflows for Performance Optimization•5 minutes
  • Demonstration: Deploying AI Models through FastAPI•7 minutes
  • Low-Code and No-Code Platforms in Decision Intelligence•5 minutes
  • Demonstration: No-Code Automation using ZAPIER•4 minutes
  • Designing Collaborative Workflows with Cross-Functional Teams•5 minutes
  • Change Management for AI-Driven Transformation•4 minutes
9 readings•Total 95 minutes
  • The Evolution of MLOps•10 minutes
  • Operationalizing Machine Learning Models•10 minutes
  • API Monitoring and Performance Analytics•10 minutes
  • Overview of RESTful APIs and Containerized AI Deployments•10 minutes
  • Serving ML Models via FastAPI•10 minutes
  • Serverless and Containerized AI: Real-World Deployment Examples•10 minutes
  • Empowering Productivity with No-Code Automation in Zapier•10 minutes
  • Organizational Benefits of Democratized Decision Intelligence•10 minutes
  • Module Summary: Scaling, Deployment, and Low-Code Adoption•15 minutes
4 assignments•Total 33 minutes
  • Knowledge Check: Scaling, Deployment, and Low-Code Adoption•15 minutes
  • Knowledge Check: MLOps for Decision Intelligence•6 minutes
  • Knowledge Check: Cloud and API-Based Decision Deployments•6 minutes
  • Knowledge Check: Low-Code AI Adoption and Business Democratization•6 minutes

This module provides a comprehensive evaluation of your understanding of the key principles, methodologies, and insights presented throughout the course, enabling you to demonstrate your proficiency through a structured graded assessment.

What's included

1 video1 reading2 assignments1 discussion prompt

1 video•Total 5 minutes
  • Course Summary•5 minutes
1 reading•Total 30 minutes
  • Practice Project: Building an AI-Powered & Event-Driven Decision Automation System•30 minutes
2 assignments•Total 60 minutes
  • End Course Knowledge Check: Automating Decision Workflows with AI•30 minutes
  • The Automation Blueprint: Scaling AI Decisions Responsibly•30 minutes
1 discussion prompt•Total 5 minutes
  • Describe Your Learning Journey•5 minutes

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Instructor

Edureka
203 Courses•185,285 learners

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Frequently asked questions

This course is designed for AI engineers, automation specialists, data scientists, and decision engineers looking to scale and operationalize AI-driven decision systems.

The course covers intelligent automation, event-driven decisioning, Generative and Agentic AI, Responsible AI governance, MLOps, cloud deployment, and low-code AI adoption.

Yes. You’ll gain hands-on experience with tools such as MLflow, Zapier, FastAPI, and cloud-based AI platforms to build and deploy automated decision systems.

You’ll learn to design automation pipelines, build adaptive AI workflows, deploy models at scale, and implement responsible AI frameworks for ethical automation.

The course is structured for approximately 3 weeks of learning, depending on your pace and engagement with projects and assessments.

Basic familiarity with Python, Decision Intelligence, and AI concepts is recommended, but guided demonstrations and low-code tools make the course accessible to non-technical learners as well.

Absolutely. You’ll explore how Generative AI enhances insight generation and how Agentic AI enables autonomous, multi-step decision-making.

Yes. A dedicated module covers fairness, accountability, transparency, and governance frameworks to ensure ethical decision automation.

You’ll complete hands-on exercises such as deploying AI models via FastAPI, automating workflows in Zapier, and building bias detection dashboards.

The course uses industry-inspired case studies spanning manufacturing, finance, and operations to show how AI automation enhances business decision-making.

Graduates can pursue roles such as AI Automation Engineer, MLOps Specialist, Decision Intelligence Architect, or AI Solutions Consultant.

As the third course in theAI-Powered Decision Intelligence specialization, it focuses on scaling and automation building on the decision modeling and optimization skills from earlier courses.

Yes. Each module includes practice assessments, and the course concludes with a graded project on deploying and optimizing an AI-powered decision automation system.

It bridges AI innovation, automation, and responsible deployment, combining technical depth with low-code accessibility, preparing professionals to lead AI-driven transformation.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.