• Admission closes

    March 11, 2026
  • Program Duration

    10 weeks
  • Learning Format

    Live, Online, Interactive

Key Features

  • Industry-Leading Collaboration With Microsoft

    Secure a joint program completion certificate from Microsoft and Simplilearn

    Earn Microsoft Learn Badges on the MS Learn Portal for MS-branded courses

  • Product Leadership and Peer Learning

    Master system design, planning, and workflows for multi-agent systems

    Connect, collaborate, and share ideas with fellow learners in real time via Slack

  • Hands-On Real-World Projects & Advanced Tools

    Build projects utilizing LangChain, CrewAI, RAG, n8n, and more

    Gain skills in deploying production-grade Agentic AI solutions

  • Simplilearn Career Service

    Strengthen your resume and get career guidance from industry specialists

    Attend mock interview sessions to help you ace the hard technical questions

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Career Opportunities

  • AI Product Manager
  • AI Automation Specialist
  • AI Strategy Consultant

AI product managers strategize, develop, and manage AI-powered products, including those leveraging multi-agent systems. They define roadmaps, coordinate engineering and data teams, and ensure alignment with business goals. These roles need an understanding of AI capabilities and product innovation.

Hiring Companies
Netflix
Bosch
Amazon
Nvidia
LinkedIn
OpenAI
Average Salary
$154KMin
$187KAverage
$280KMax

Essentials Skills You will Develop

  • Agentic Frameworks
  • UIUX Agentic AI
  • MultiAgent Systems
  • Planning Systems
  • Prompt Engineering
  • RAG
  • Workflow Automation
  • Copilots
  • Ethics and Transparency
  • GTM for Agentic AI
  • Intelligent Automation
  • LLM Function Calling
  • MCP

Earn Professional Certifications

After a successful program completion, you will earn a joint certificate from Microsoft and Simplilearn. You will also secure Microsoft Learn badges on the Microsoft Learn portal for the Microsoft-branded courses.

Program Certificate
Program Certificate
  • Joint program completion certificate from Microsoft and Simplilearn
  • Individual course completion certificates from Simplilearn
Microsoft Certificate
Microsoft Certificate
  • MS Learn Badge on the MS Learn Portal for the MS-branded course
  • Latest AI agents course content by Microsoft
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Program Curriculum

This Agentic AI program offers an end-to-end learning path across AI foundations, generative AI, LLM internals, and multi-agent systems. Learners build practical expertise in agent design, planning frameworks, and go-to-market strategy to drive AI product innovation.

  • Start your learning journey with a comprehensive introduction to the program. This module provides an overview of the curriculum, learning objectives, and key outcomes while exploring how AI and generative AI and Agentic AI are transforming industries.

  • This module revisits Python programming essentials tailored for AI/ML applications. It covers core constructs, environment setup across IDEs and cloud platforms, data structures, control flow, OOP basics, file handling, and AI-powered code generation with GitHub Copilot. Hands-on exercises focus on real-world data tasks and culminate in a capstone comparing traditional and AI-assisted coding.

  • This course introduces the Learn > Build > Deploy framework and covers AI hierarchy distinctions (AI, ML, DL, GenAI, Agentic AI), transformer architectures, and autonomous AI agents. Topics include key papers like "Attention is All You Need," CoT prompting, ReAct frameworks, and a 4-layer GenAI stack analogy. It establishes foundational knowledge critical to technical product management of AI systems, with an emphasis on theoretical and applied agentic AI concepts.

  • This deep dive explores the 4-layer GenAI technology stack—Infrastructure, Model, Orchestration, and Application—with emphasis on scalability, cost, and product lifecycle management. It covers cloud platforms and vector databases, foundation models and fine-tuning, agent frameworks and workflows, and low-code prototyping with UX design principles. The course also builds prompt engineering mastery using zero-shot, CoT, and ReAct techniques through hands-on demos.

  • Focusing on PM productivity with AI, this module teaches prompt engineering principles and planning systems using LangChain and function calling APIs. It includes live sessions building Q&A bots integrating APIs, planning workflows with agents, and advanced prompt strategies to optimize interaction with language models. Labs guide the development of multi-step agents and contextual tool integration, enhancing practical skills in agent-based product development.

  • This course explores advanced retrieval-augmented generation (RAG) systems and multi-agent architectures through hands-on implementation with CrewAI and LangGraph. It details agent collaboration patterns, role-based architectures using YAML, memory strategies, and real-world orchestration frameworks. Learners build modular multi-agent teams focusing on scalability, state management, and autonomous information synthesis. Deliverables include pitches advocating modular agent architectures.

  • Building on foundational multi-agent knowledge, this course delves into enterprise-grade agent orchestration using Microsoft AutoGen and n8n workflow automation. Covered are communication protocols, database integration, and production deployment strategies. Projects include developing marketing agent pipelines with attention to scalability, performance, security, and compliance. Visual workflows and protocol deep dives support mastery of complex distributed agent ecosystems.

  • This module introduces the Model Context Protocol (MCP) for integrating and standardizing AI tools. Topics include structured context binding, interoperability standards, JSON schema design, secure tool hosting, and memory persistence. Labs develop contextual AI agents chaining outputs across tools with authentication and performance optimization. Emphasis is on enterprise readiness, security best practices, and tool discoverability through standardized protocols.

  • Offering a comprehensive framework, this course teaches measurement of AI agent performance using OKRs, key indicators like success rate and latency, and ROI calculations. It covers observability tooling with LangSmith and Phoenix, real-time logging, and conversational analysis. Business strategy topics include pricing, go-to-market planning, and deployment of agent MVPs with analytics dashboards. Practical instrumentation and monitoring equip learners for operational excellence.

  • Centering user experience for AI products, this module covers interaction design patterns for agentic UX, including flexible, probabilistic flows, ambiguity handling, and human-in-the-loop checkpoints. It addresses ethical risks such as hallucinations and bias and teaches guardrail implementations and transparency techniques like confidence disclosures and explainability interfaces. Learners create complete UX prototypes emphasizing trust, user control, and fail-soft design.

  • Focused on deployment and live operations, this course examines cloud vs edge hosting, serverless and containerized environments, and model hosting strategies. It includes hands-on Firebase and n8n automation workflows, feedback and testing system integrations for user insights, alert configurations for monitoring, and infrastructure-as-code introductions with Terraform and Pulumi. The course prepares learners for scalable, maintainable AI product readiness.

  • This course focuses on building AI agents leveraging Microsoft Azure’s cloud infrastructure and toolset. It covers Azure-specific frameworks, deployment workflows, security integration, and scalable orchestration techniques. Learners gain hands-on experience developing and hosting AI agents in the Azure ecosystem with attention to enterprise-grade reliability and compliance.

  • The capstone integrates multi-agent system design and go-to-market planning through a production-grade project building a 4-agent market research and GTM framework using n8n and CrewAI with MCP integration. It emphasizes business strategy development, including Lean Canvas, pricing models, and acquisition strategies, alongside instrumented agent performance data and real-world chatbot deployment. This synthesis project prepares learners for practical AI product leadership.

ELECTIVES
  • This course prepares you to build AI solutions on Azure using Microsoft Foundry. You’ll plan and set up AI environments, select and deploy models from the model catalog, build apps with the Foundry SDK, use prompt flow, develop RAG solutions with your data, fine-tune models, apply responsible AI practices, and evaluate generative AI performance using Azure AI Studio tools.

  • This masterclass offers exposure to designing and deploying agentic AI solutions using modern low-code and open-source frameworks. Delivered through live sessions led by industry experts, it showcases how Copilot Studio and AutoGen can accelerate development and enable rapid deployment of agentic systems in real-world business environments.

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29+ Tools Covered

MS-AGI-Asana
MS-AGI-AutoGen
MS-AGI-AutoGPT
MS-AGI-ChatGPT
MS-AGI-CrewAI
MS-AGI-Docker
MS-AGI-Emergent
MS-AGI-FastMCP
MS-AGI-Figma
MS-AGI-Github-Copilot
MS-AGI-GitHub
MS-AGI-Gmail
MS-AGI-Google-Colab
MS-AGI-Google-Docs
MS-AGI-Jupyter
MS-AGI-LangChain
MS-AGI-LangGraph
MS-AGI-LangSmith
MS-AGI-Lovable
MS-AGI-MCP
MS-AGI-MetaGPT
MS-AGI-Miro
MS-AGI-MongoDB
MS-AGI-n8n
MS-AGI-Phoenix
MS-AGI-Pinecone
MS-AGI-Postgre-SQL
MS-AGI-Slack
MS-AGI-Visual-Studio-Code

Industry Projects

Still have questions?

Our dedicated team is prepared to answer them.

Total Program Fee

Program Fee $ 2,699

Pay in Installments

As low as

You can pay monthly installments using Splitit or Klarna.These plans are offered with low APR and no hidden fees.

Program Cohorts

Who Is This Program For?

How To Apply

  • 1
    Submit Application

    Complete the application by providing the essential details about yourself

  • 2
    Reserve Your Seat

    Secure your seat by completing the program fee payment

  • 3
    Start Learning

    Begin your learning journey on the designated cohort start date

Start Application

Career Support

Simplilearn Career Assistance

Simplilearn’s Career Services program, offered in partnership with Prentus, is a service that helps you to be career-ready for the workforce and land your dream job in U.S. markets.
Access to workshops, networking tools, and community support

Access to workshops, networking tools, and community support

Stay on top of your job hunt with a smart tracker and job board

Stay on top of your job hunt with a smart tracker and job board

Build an ATS-friendly resume using the AI Resume Builder

Build an ATS-friendly resume using the AI Resume Builder

Practice anytime with the AI-powered Mock Interview Coach

Practice anytime with the AI-powered Mock Interview Coach

Demand For Program

Demand for Agentic AI and Multi-Agent Systems expertise at mid-to-senior-level roles among product managers, designers, and tech leaders is robust and growing in both the US and India. Agentic AI is fueling innovations in autonomous systems, complex decision-making, and digital transformation strategies. Market analysis shows mid-level AI Product Managers in India typically earn Rs 19–36 L, with salaries reaching up to Rs 50 L at senior levels. In the US, compensation often exceeds $120K. Enterprises are increasingly seeking professionals capable of orchestrating multi-agent approaches across products, especially as AI product leadership and AI-native architectures become crucial to product success. Startups and established firms alike are increasing investments in this skill set, supported by the growing number of educational programs. As AI moves from experimentation to widespread adoption, agentic AI and multi-agent systems expertise signal readiness to lead this business transformation, ensuring long-term career resilience and leadership at the cutting edge of AI innovation.

Demand For Program

Program FAQs

  • What is the Agentic AI course in collaboration with Microsoft?

  • Who is this Applied Agentic AI training designed for?

  • What makes this Applied Agentic AI program unique?

  • Who should consider enrolling in this Applied Agentic AI program?

  • Do I need prior AI or machine learning experience to join the Agentic AI course?

  • Are beginners eligible for this Agentic AI training program?

  • Is this Applied Agentic AI program suitable for non-technical professionals?

  • What skills will I gain from this Agentic AI training?

  • Is the Agentic AI program recognized by the industry?

  • Can I pursue this Agentic AI training while working full-time?

  • How interactive is the Agentic AI course—are the sessions live or recorded?

  • Is there an admission or selection process for this Agentic AI program?

  • How will this Applied Agentic AI certificate help in advancing my career?

  • Does this Applied Agentic AI program include career guidance or mentoring support?

  • What is the refund or cancellation policy for the Agentic AI course?

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