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Agentic AI For Beginners
Master how AI systems can reason, plan and act autonomously. Build your own AI agents—no experience needed. Transform your future today.
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Course overview
Master the Foundations of AI Agents
Step into the future of artificial intelligence with our 5-week cohort-based course on Agentic AI. Discover how to create autonomous, adaptive AI systems that can reason, plan, and act independently. Unlike traditional AI models, you'll learn to design and deploy intelligent agents that solve complex problems with minimal human intervention.
Through expert-led sessions, immersive lab exercises, and Saturday live Q&A sessions, you'll master proven agentic frameworks and design patterns. Build AI systems that are not just powerful, but scalable, trustworthy, and ready for production environments.
Perfect for beginners and professionals alike, this course transforms theoretical concepts into practical skills. Join us to harness the revolutionary potential of AI agents and position yourself at the forefront of the next wave of technological innovation.
Who is this course for
01
Curious tech enthusiasts eager to understand AI fundamentals without prior coding experience who want to build practical automated solutions
02
Business professionals seeking to implement intelligent automation in their workflows who need a practical understanding of AI Agents.
03
Students and career-switchers exploring emerging tech opportunities who want hands-on experience with Agents and AI systems.
What you’ll get out of this course
Master the Fundamentals of AI Agents
Remember & Understand core AI agent concepts, including agentic frameworks, design principles, and real-world use cases, to build a strong foundation.
Apply Agentic Design Patterns to Build AI Agents
Apply key frameworks such as Tool Use, Planning, Multi-Agent Systems, and Metacognition to create AI agents that adapt, learn, and interact autonomously.
Evaluate & Optimize AI Agent Performance
Analyze & Evaluate AI agent efficiency, scalability, and ethical considerations to ensure responsible and trustworthy AI development.
Design & Deploy Production-Ready AI Agents
Create AI-driven solutions that can operate independently in real-world applications, enhancing automation and intelligent decision-making.
What’s included
Live sessions
Learn directly from your instructors in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
7 live sessions • 39 lessons • 11 projects
Week 1
- 📄
Let's Get Ready to Build AI Agents!
Complete by May 17 - ✍️
Introduce Yourself in the Community
Submit by May 11 - 📄
Agentic AI Kickoff Replay
Pre-Course Setup Guide
May
10
Agentic AI Course Kickoff
Kickoff Replay
Week 2
- 📄
Defining AI Agents, Their Types & Use Cases
- 📄
When to Use AI Agents
- 📄
Basics of Agentic Solutions
- ✍️
Test: Introduction to Agentic AI
Submit by May 18 - 🌐
Exploring Agentic AI Frameworks with Noelle and Skye
- 📄
Unlocking the Power of AI Agent Frameworks
- 📄
How to Quickly Prototype, Iterate, and Improve AI Agents
- 📄
Understanding the Differences Between AutoGen, Semantic Kernel, and Azure AI Age
- 📄
Azure AI Agent Service – Scalable AI Deployment in the Cloud
- 📄
Choosing the Right AI Agent Framework
- ✍️
Test: Exploring Agentic Frameworks
Submit by May 18 - 📄
Lab Setup Session - Part 1
- 📄
Lab Setup Part 3
🤖 Introduction to Agentic AI
This course gives you fundamental knowledge and applied samples for building with AI Agents.
Exploring Agentic Frameworks
May
17
Agentic AI Q&A - Session 1
Lab Review Session 1
May
16
Lab Set-up Session - Part 3
Lab Setup Part 3
Week 3
- 📄
Webinar: Agentic AI Design Principles
- 📄
The Agentic Design Principles: Building AI Agents That Work for Humans
- 📄
Implementing Agentic Design Principles: Guidelines for Practical AI Design
- ✍️
Test: Understanding AI Agentic Design Principles
Submit by May 25 - 📄
The Tool Use Design Pattern: Enhancing AI Agents with External Tools
- 📄
Building AI Agents with the Tool Use Design Pattern: Essential Components
- 📄
Tool Use Design Pattern in Action: Implementing with Agentic Frameworks
- 📄
Example: Tool Use Design Pattern with N8N
- ✍️
Test: How to Leverage the Agent Tool Use Design Pattern
Submit by May 25
Understanding AI Agentic Design Principles
How to Leverage the Agent Tool Use Design Pattern
May
24
Agentic AI Q&A - Agentic Design Patterns and Tool Use
Week 4
- 📄
Webinar- Introduction to Agentic RAG
- 📄
Introduction to Agentic RAG
- 📄
Grasp Iterative Maker-Checker Styled lesson
- 📄
Explore Practical Applications
- ✍️
Test: Understanding Agentic RAG
Submit by Jun 1 - 📄
How to build and deploy safe and effective AI Agents
- 📄
Important security considerations when developing AI Agents.
- 📄
How to maintain data and user privacy when developing AI Agents.
- ✍️
Test: Building Trustworthy Agents
Submit by Jun 1
Understanding Agentic RAG
Building Trustworthy Agents
May
31
Agentic AI Q&A - Agentic RAG & Trustworthy Agents
Week 5
- 📄
Defining Goals and Breaking Down Tasks
- 📄
Structured Output & Dynamic Planning
- ✍️
Test: Planning & Design Patterns
Submit by Jun 1 - 📄
Identify scenarios where multi-agents are applicable
- 📄
Recognize the advantages of using multi-agents over a singular agent.
- 📄
Comprehend the building blocks of implementing the multi-agent design pattern.
- ✍️
Test: Designing Multi-Agent Solutions
Submit by Jun 8
🪄 AI Agents: Planning & Design Patterns
📃Designing Multi-Agent Solutions
Jun
7
Agentic AI Q&A - Session 4
Week 6
- 📄
🧠 Introduction to Metacognition in AI Agents
- 📄
🗺️ Planning as a Core Function of AI Agent Behavior
- 📄
📚 Understanding the Corrective RAG System
- 📄
🎯 Evaluating Relevancy and Searching with Intent in AI Agents
- ✍️
Test: Understanding Metacognition in AI Agents
Submit by Jun 15 - 📄
🧠 How to Evaluate AI Agents for Aligned, Effective Performance
- 📄
🛠 Troubleshooting Common AI Agent Issues
- 📄
💰 Managing the Cost of Deploying AI Agents
- ✍️
Test: AI Agents in Production
Submit by Jun 15
Understanding Metacognition in AI Agents
AI Agents in Production
Jun
14
Agentic AI Q&A - Session 5
Model Context Protocol (MCP) Integration
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Meet Your Instructors
Noelle Russell
Noelle Russell
Noelle Russell is a multi-award-winning speaker, author, and AI Executive who specializes in transforming businesses through strategic AI adoption. She is a revenue growth + cost optimization expert, 4x Microsoft Responsible AI MVP, and named Top 25 Agentic AI Leaders |in 2025. She has led teams at NPR, Microsoft, IBM, AWS and Amazon Alexa, and is a consistent champion for Data and AI literacy and is the founder of the "I ❤️AI" Community teaching responsible AI for everyone.
Skye Mann-Evans
Skye Mann-Evans
Skye Mann-Evans is a Global AI & Digital Transformation Executive with over 20 years of experience helping organizations navigate change and drive innovation. Her expertise spans AI strategy, business and technology consulting, leadership development, and program/product management. Skye is a passionate advocate for AI literacy and digital reinvention, equipping leaders and professionals with the tools to thrive in a rapidly evolving world. Through her work, she empowers audiences to harness AI to elevate human intelligence, decision-making, and creativity—unlocking growth and transformation.
Padmini Soni
Padmini Soni
Padmini Soni is the Head of Responsible AI Growth at the AI Leadership Institute and Founder of Rezonance AI, a consulting firm guiding businesses to adopt AI responsibly. With over 25 years of experience bridging technology and business, she specializes in AI strategy, ethical governance, and transformation. As co-founder of AWAAI, she supports mentorship for women in AI. Co-author of an upcoming book on OpenAI GPT Builders, Padmini is passionate about AI literacy, delivering workshops, speaking, and advising on ethics, fairness and transparency.
Uvika Sharma
Uvika Sharma
Uvika Sharma is a visionary Data & AI Strategist with over 20 years of experience, having worked at leading organizations like Pfizer, Accenture, S&P, Moody’s, and Citi. As the founder of INTLDA, she helps businesses implement AI responsibly and also leads advisory efforts at AI 2030. She is the co-founder of Asian Women Advancing AI and an active mentor in the Break Through Tech AI Program at Cornell Tech, supporting the next generation of women in AI.
Course schedule
4-6 hours per week
Saturday Q&A
11:00 am- 12:00pm EST
Join us every Saturday to discuss the project work, session topic and review recorded sessions! Also a great chance to network with fellow students.
Weekly projects
2 hours per week
Every week you will have projects to allow you to put your fingers on the keyboard and build something awesome and agentic.
Learning is better with cohorts
Active hands-on learning
This course builds on live Q&A sessions, on-demand learning, and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you