Organizations now use multi-agent systems for customer support, financial analysis, supply chain monitoring, legal research, content workflows, and workplace automation. These systems combine tools such as CrewAI, LangGraph, Microsoft Copilot Studio, RAG, Agentic RAG, memory, tool calling, and human review to divide work across specialized AI agents and improve task completion.
For working professionals, the main challenge is no longer awareness. The challenge is choosing the right way to learn and apply agentic workflows. Free courses, no-code programs, technical certificates, and postgraduate options serve different goals, which often creates confusion.
Great Learning addresses this gap through a structured roadmap. Beginner courses explain agent concepts and frameworks. Intermediate programs focus on applied workflows and projects. Advanced university-backed programs cover orchestration, MCP, evaluation, security, governance, and deployment.
Which Great Learning Agentic AI Course Fits Your Background?
You should choose a course based on your current role, coding experience, and expected outcome. A business leader needs strategy and governance knowledge, while a developer needs frameworks, RAG, orchestration, evaluation, and deployment skills.
The table below helps you identify the most relevant option.
| Your Background | Recommended Courses or Programs | Access | Level |
|---|---|---|---|
| You are new to AI or work in a business role |
|
Free and Pro+ | Beginner |
| You want to build no-code workplace workflows |
|
Paid | Beginner to Applied |
| You want technical or architectural depth |
|
Paid | Advanced |
If You Are New to AI or Come From a Non-Technical Background
Start here when you need to understand how AI agents work before building workflows or studying technical frameworks. These courses help you understand planning, reasoning, memory, business use cases, risks, governance, and human oversight.
Getting Started With Agentic AI, Great Learning Academy
Access: Free
Level: Beginner
Technical Requirement: No coding experience required
Great Learning
Getting Started With Agentic AI
Learn the fundamentals of AI agents, multi-agent systems, and agentic workflows. Start building AI-powered projects with no coding required.
3 Hrs
Online
Free Course
Guided Project Included
Getting Started With Agentic AI introduces you to the core components of autonomous AI systems. You learn how an AI agent works toward a goal, selects actions, uses memory, and responds to changing information.
This Free Agentic AI Course also covers planning, reasoning, execution, decision-making, agent design patterns, risks, and limitations. It also explains why you need clear goals, controlled tool access, guardrails, and human review when building agentic workflows.
- Delivery and Duration: Online, self-paced, 3.0 learning hours.
- Credentials: You receive access to the course content for free. A completion certificate is available after successful completion and payment of the applicable certificate fee. The credential is a course completion certificate, not a university certificate.
Best Suited For:
- You are exploring agentic AI for the first time.
- You are considering a career shift into AI.
- You want to understand AI agent terminology.
- You need a foundation before learning frameworks.
- You want to assess agentic AI use cases.
What You Will Learn:
- How AI agents differ from standard AI assistants
- How agents plan, reason, act, and use memory
- Where agentic AI fits into business processes
- Which risks affect autonomous workflows
- Why guardrails and human supervision matter
Why Should You Pick This Course?
Pick this course when you need a short and accessible introduction. You will gain enough conceptual knowledge to understand more applied topics such as orchestration, tool use, agent communication, and shared memory.
Agentic AI and Leadership Transformation, Great Learning Academy
Access: Free
Level: Beginner
Technical Requirement: No coding experience required
Great Learning
Agentic AI and Leadership Transformation
Learn how AI agents support business operations and leadership decisions with practical, hands-on guidance.
1.5 Hrs
Free
Rating: 4.8/5
20,000+ Learners
Agentic AI and Leadership Transformation helps you understand AI agents from a business and leadership perspective. The course focuses on how you evaluate AI opportunities, connect agentic systems with business goals, and manage adoption across teams.
You will learn generative AI strategy, leadership decisions, organizational transformation, AI-powered operations, and governance. This free Agentic AI and Leadership course also helps you examine how people, processes, data, technology, and approval systems affect AI implementation.
Delivery and Duration: Online, self-paced, 1.5 learning hours.
Credentials: You receive access to the course content for free. A completion certificate is available after successful completion and payment of the applicable certificate fee.
Best Suited For:
- You lead a team or business function.
- You evaluate AI projects or tools.
- You work in consulting or product management.
- You manage digital transformation initiatives.
- You need AI knowledge without programming.
What You Will Learn:
- How agentic AI supports business operations
- How you identify processes suited to AI agents
- How you evaluate agentic AI opportunities
- How you discuss AI initiatives with technical teams
- How governance and workforce decisions affect adoption
Why Should You Pick This Course?
Pick this course when your role focuses on strategy, business value, adoption, or governance. You will learn how to assess agentic AI initiatives without moving into technical implementation.
Building Intelligent AI Agents, Great Learning Academy
Access: Free
Level: Beginner to early technical
Technical Requirement: Basic Python knowledge is helpful
Great Learning
Building Intelligent AI Agents
Learn to build and coordinate AI agents using frameworks like CrewAI and LangGraph with practical guided projects.
3 Hrs
Self-Paced
1 Guided Project
7-Day Free Trial
Building Intelligent AI Agents introduces you to CrewAI and LangGraph. CrewAI supports role-based collaboration between several agents. LangGraph helps you organize workflows through states, actions, decisions, and handoffs. You will also learn about agent autonomy, decision models, conversational agents, design patterns, workflow logic, and multi-agent collaboration. This Free AI Agents Course connects basic agent concepts with introductory technical implementation.
Delivery and Duration: Online, self-paced, three learning hours.
Credentials: You receive access to the course content for free. A completion certificate is available after successful completion and payment of the applicable certificate fee.
Best Suited For:
- You know basic Python.
- You are a developer entering agentic AI.
- You are studying software or AI.
- You want introductory framework exposure.
- You are preparing for hands-on agent projects.
What You Will Learn:
- How several agents divide responsibilities
- How agents exchange information
- How CrewAI supports role-based workflows
- How LangGraph manages workflow states
- How you define agent roles, tasks, and handoffs
Why Should You Pick This Course?
Pick this course when you want to move from theory to basic technical implementation. You will gain introductory exposure to two commonly used agent frameworks without committing to a longer program.
Building Agentic Workflows With Microsoft Copilot, Great Learning Academy Pro+
Access: Paid through Academy Pro+
Level: Beginner to applied
Technical Requirement: Suitable for Microsoft users, analysts, and developers
Great Learning
Building Agentic Workflows With Microsoft Copilot
Learn to create AI agent workflows using Microsoft 365, GitHub Copilot, and Copilot Studio with hands-on projects for workplace automation.
3 Hours
Guided Project
Beginner to Applied
7-Day Trial
Building Agentic Workflows With Microsoft Copilot focuses on AI agents across Microsoft 365, GitHub Copilot, and Copilot Studio. You first study generative AI, large language models, grounding, Microsoft Graph, Semantic Index, and RAG. RAG, or retrieval-augmented generation, helps an AI system retrieve approved information before producing an answer.
You then explore Copilot across Word, Excel, PowerPoint, and Outlook. You also study GitHub Copilot for coding, testing, debugging, and refactoring. This Microsoft Copilot course covers custom agents, data connectors, connected agents, privacy, security, governance, and deployment.
Delivery and Duration: Online, self-paced, three hours, with one guided project.
Credentials: Course and project certificates are available through the applicable Pro+ subscription.
Project Experience: You work on a supply chain scenario involving delays, supplier issues, operational risks, and cross-functional response planning.
Best Suited For:
- You use Microsoft 365 at work.
- You work as a business analyst.
- You develop or test software.
- You manage operations or projects.
- You want to build agents through Copilot Studio.
What You Will Learn:
- How to use Copilot across Microsoft 365
- How to use GitHub Copilot for development tasks
- How to build custom agents in Copilot Studio
- How to connect agents with business data
- How RAG improves grounded responses
- How privacy and governance affect deployment
Why Should You Pick This Course?
Pick this course when you want to apply AI agents within Microsoft tools. You will move from basic concepts to a guided workplace project without taking a long technical program.
If You Want to Build No-Code Workplace Workflows
Choose this option when you want to automate research, communication, content, reporting, and routine tasks without studying Python or agent frameworks in depth.
AI-Native Professional: Workflows and Agents for Productivity
Access: Paid professional program
Level: Beginner to applied
Technical Requirement: No coding required
AI-Native Professional is a 6-week online program focused on practical AI workflows. You move from using individual generative AI tools to building connected systems for research, content, communication, and workplace productivity.
You create prompt systems, document research assistants, multi-tool content pipelines, trigger-based automations, and specialized business agents. This AI Agents Course also includes tools such as ChatGPT, Claude, Gemini, Perplexity, Gamma, Google Vids, HeyGen, Lovable, and Activepieces.
Delivery and Duration: Online, 6 weeks, with live sessions, weekly deliverables, and capstone projects.
Credentials: You receive a Professional Certificate from Great Learning after successful completion.
Project Experience: You complete weekly assignments and a final capstone focused on research, content, business intelligence, or productivity.
Best Suited For:
- You work in marketing.
- You work in HR or recruitment.
- You work in finance or sales.
- You manage business operations.
- You work as a consultant or manager.
- You want practical AI skills without coding.
What You Will Learn:
- How to build reusable prompt systems
- How to create document research assistants
- How to connect several AI tools
- How to automate trigger-based tasks
- How to build role-specific business agents
- How to present a working AI workflow
Why Should You Pick This Program?
Pick this program when your goal is to improve your current work through no-code systems. You will complete practical projects instead of focusing on advanced AI architecture.
If You Are a Developer, AI Professional, or Technical Leader
Choose this path when you want deeper knowledge of RAG, MCP, agent architecture, orchestration, evaluation, security, governance, and deployment.
These programs require more study time and provide university-backed or postgraduate credentials.
IIT Bombay Certificate in Agentic AI
Access: Paid university certificate program
Level: Advanced
Technical Requirement: Best suited to software, data, and AI professionals
The IIT Bombay Certificate in Agentic AI focuses on designing, coordinating, and deploying AI agents. You will learn Python, large language models, RAG, GraphRAG, vector databases, function calling, tool integration, router patterns, CrewAI, LangGraph, ReAct, Chain-of-Thought, and MCP. The Model Context Protocol (MCP) provides a structured way to connect AI systems with tools, databases, and external services. This Agentic AI Course also covers multi-agent orchestration, cost optimization, governance, human-in-the-loop controls, and scalable deployment.
Delivery and Duration: Online, 5-months, with live faculty sessions. You should plan for four to six hours of study each week.
Credentials: You receive a Certificate of Completion from IIT Bombay after meeting the required evaluation criteria.
Project Experience: Projects include a financial news analyst agent and a RAG-based customer support system.
Best Suited For:
- You work as a software developer.
- You work in data or AI.
- You are an AI engineer.
- You work in technology consulting.
- You lead technical AI projects.
What You Will Learn:
- How to design agents that plan and use tools
- How to build RAG and GraphRAG systems
- How to coordinate agents with CrewAI and LangGraph
- How to connect agents through MCP
- How to apply cost and governance controls
- How to prepare agentic systems for deployment
Why Should You Pick This Program?
Pick this program when you want focused technical depth in agentic AI. You will study the frameworks, protocols, retrieval systems, and controls required to build and deploy multi-agent applications.
Johns Hopkins University Applied Generative AI and Agentic AI
Access: Paid university certificate program
Level: Advanced
Technical Requirement: Suitable for technology professionals and technical career-switchers
The Johns Hopkins University program combines agentic AI with broader generative AI study. You will learn Python, machine learning, large language models, prompt engineering, embeddings, vector databases, RAG, advanced RAG, fine-tuning, model evaluation, AI-assisted coding, memory, tool use, ReAct, MCP, and multi-agent systems.
This Generative AI Course also covers hallucination measurement, bias, safety, security, regulations, reliability, and cost management.
Delivery and Duration: Online, 16 weeks, with recorded lessons, live sessions, faculty masterclasses, and a hands-on lab environment.
Credentials: You receive a Certificate of Completion and 11 Continuing Education Units from Johns Hopkins University.
Project Experience: Projects cover personal finance, clinical decision support, and AI-supported legal research.
Best Suited For:
- You are a developer or data scientist.
- You work in machine learning or AI.
- You want broader generative AI knowledge.
- You are moving into a technical AI role.
- You want experience across several application areas.
What You Will Learn:
- How to build generative AI applications
- How to create basic and advanced RAG workflows
- How to design single-agent and multi-agent systems
- How to evaluate retrieval and model outputs
- How to apply safety, security, and reliability controls
- How to build an applied AI project portfolio
Why Should You Pick This Program?
Pick this program when you want agentic AI within a wider generative AI curriculum. You will study multi-agent systems alongside RAG, fine-tuning, evaluation, responsible AI, and application development.
McCombs School of Business at The University of Texas at Austin Post Graduate Program in AI Agents and Generative AI for Business Applications
Access: Paid postgraduate program
Level: Advanced
Technical Requirement: Suitable for technical and non-technical professionals through separate tracks
This AI Agents for Business connects AI agent development with business workflows and enterprise decisions. You choose between a Python-based Code Track and a tools-based No-Code Track.
Both tracks cover generative AI, large language models, prompt engineering, RAG, Agentic RAG, vector databases, agent architecture, memory, tool use, MCP, ReAct, multi-agent systems, human feedback, security, grounding, and validation. Agentic RAG gives an AI agent greater control over retrieval decisions, source selection, and the use of retrieved information.
Delivery and Duration: Online, 13 weeks, with weekly live mentorship and faculty masterclasses.
Credentials: You receive a Certificate of Completion and Continuing Education Units from the McCombs School of Business at The University of Texas at Austin.
Project Experience: Projects include support ticket categorization, financial report analysis, delivery exception handling, and a multi-agent retail chatbot.
Best Suited For:
- You lead a business or product function.
- You work as a developer or technical leader.
- You work in consulting.
- You want a code or no-code track.
- You want to apply AI agents to business workflows.
What You Will Learn:
- How to identify useful business applications for AI agents
- How to build workflows through code or no-code tools
- How to develop RAG and Agentic RAG systems
- How to design multi-agent business workflows
- How to apply evaluation, security, and human feedback
- How to build an e-portfolio across business functions
Why Should You Pick This Program?
Pick this program when you want to connect technical agent development with business implementation. The two-track format helps you choose a study route based on your coding background.
How to Choose the Right Learning Stage
- Choose the beginner stage when you have limited knowledge of AI agents. The beginner courses explain terminology, business applications, frameworks, and basic multi-agent workflow structures.
- Choose the intermediate stage when you understand agent fundamentals and want to build practical workplace workflows. These options focus on Microsoft Copilot, no-code automation, connected tools, and project work.
- Choose the advanced stage when you want deeper knowledge of architecture, RAG, MCP, orchestration, security, evaluation, and deployment. These programs suit learners pursuing technical roles, leadership responsibilities, or university-backed credentials.
Conclusion
Learning multi-agent systems works best through a structured progression. Beginner courses establish the foundation through agent concepts, planning, reasoning, memory, business use cases, CrewAI, and LangGraph.
Intermediate programs help learners apply those concepts through workplace automation, connected tools, RAG, no-code workflows, and guided projects.
Advanced university-backed programs provide deeper knowledge of multi-agent orchestration, MCP, Agentic RAG, security, evaluation, governance, and deployment. Choose the stage that matches your technical background, professional role, and expected learning outcome.