Agentic AI Systems: Build, Deploy & Scale
Master AI with experts from IBM, Intel, IRS & More
- Design production-ready Agentic Al systems with LangGraph and CrewAI
- Develop Agentic AI systems with Harness Engineering & Agent Swarms
- Learn to deploy and secure systems with guardrails & observability
- Create a job-ready AI portfolio with 8+ production-ready Al projects
Industry Partner:
Talk to an advisor :
+1-844-532-7688
Talk to an advisor :
+1-844-532-7688- Admission closesOct 21, 2026
- Program Duration8 weeks
- Learning FormatLive, Online, Interactive
Key Features
Columbia Engineering Advantage
Earn a certificate from Columbia Engineering Executive Education and Simplilearn
Attend a quarterly live academic masterclass led by Columbia Engineering faculty*
Build Production-Ready Al
Develop hands-on skills in Agentic RAG, MCP & multi-agent systems
Master Agentic Al lifecycle - foundations, engineering, orchestration & deployment
Applied Learning
Build 8+ hands-on projects, including a production-ready Agentic AI capstone
Work with 20+ latest tools such as LangGraph, CrewAI, MCP and OpenClaw
Simplilearn Career Services
Strengthen your resume and get career guidance from industry specialists
Attend mock interview sessions to help you ace the hard technical questions
Need to know more?
Need to know more?
Talk to an Advisor
Toll Free : +1-844-532-7688
Corporate Training
Enroll your employees into this program, NOW.
Talk to an Advisor
Toll Free : +1-844-532-7688
Career Opportunities
- Agentic AI Engineer
- Applied AI Engineer
- AI Agent Developer
Agentic AI Engineer
An Agentic AI Engineer designs, builds, and deploys production-ready AI systems. This role involves agent orchestration, workflow design, tool integration, evaluation, guardrails, observability, and optimizing agentic systems for reliability & security. (Source: Glassdoor)
Essential Skills You Will Develop
- Agent Memory Management
- Agent Swarm Design
- Agentic Al Architecture
- Agentic Al Engineering
- Agentic RAG
- Al Agent Evaluation
- Al Governance
- Al Guardrail Implementation
- Al Observability
- Al Workflow Automation
- Cloud Al Deployment
- Harness Engineering
- Loop Engineering
- Model Context Protocol
- Production Al Operations
- Multi Agent Orchestration
Earn Professional Certifications
Upon successful completion of the program, you'll receive a program completion certificate from Columbia Engineering Executive Education, in partnership with Simplilearn to show you can build production-ready Agentic AI systems and unlock new opportunities in the rapidly evolving Agentic AI landscape.
A Hallmark of Excellence- Build a showcase-ready Agentic AI portfolio by completion
- Gain confidence designing and deploying production-ready AI agents
Gain an Industry Edge- Learn to develop Al agents on Azure
- Course completion certificate hosted on the Microsoft Learn portal
Program Curriculum
Master the full lifecycle of building and operating agentic AI systems, from foundations and agent architecture to orchestration and production deployment. Over 8 weeks, you’ll progress from building AI agents and multi-agent systems — culminating in a production-ready Agentic AI capstone project.
- Program On-BoardingBegin with an introduction to the program structure, curriculum, learning outcomes, and support system. This induction outlines the key concepts and skills learners will develop throughout the program.
- Getting Started with Agentic AIThe Getting Started section is your first stop in the LMS, designed to help you understand the program structure, learning experience, and what to expect before you begin.
- Building Blocks of Agentic AIBuild the conceptual foundation for Agentic AI by understanding how AI, LLMs, reasoning, tools, and autonomy come together to create agents. The module introduces the Learn → Build → Deploy approach and the complete AI Agent Lifecycle, including context engineering, evaluation, observability, and governance.
- Prompt Engineering & the Internals of Learning AlgorithmsLearn prompt engineering techniques to generate more reliable AI outputs, understand how learning algorithms enable AI systems to learn from data, and apply this knowledge to interact with AI more effectively and optimize results.
- Workshop: Al Agents in ActionLearn to build AI-powered workflows with n8n using triggers, actions, app integrations, data mapping, and AI nodes, then apply these skills through hands-on projects across sales, product feedback, and e-commerce.
- Generative Al Applications & AgentsDevelop model-layer fluency by understanding the capabilities and limitations that directly impact AI products and agents. Learners build an AI product, work with function calling and MCP, implement a RAG pipeline, evaluate it with RAGAS, and deploy it on Hugging Face Spaces.
- Programming with OpenAlLearn to program practical Generative AI applications using OpenAI APIs, LLMs, LangChain, and multimodal AI. Explore how to build applications that work with text, data, images, audio, and video through hands-on exercises and applied assignments.
- Designing Multi-Agent Al SystemsMove from building individual agents to designing complete agent systems. Learners build Agentic RAG and multi-agent workflows using LangGraph and CrewAI while exploring orchestration patterns, A2A communication, failure handling, and the trade-offs involved in production-grade systems.
- Architect Modern Al Agents with Harness EngineeringLearn Harness Engineering, the discipline of designing and operating the complete system around an AI model. Using real open-source systems such as Hermes, Claude Code, OpenClaw, LangGraph, and OpenAI Agents SDK, learners explore the layers that govern agent behavior, security, evaluation, and continuous improvement.
- Workshop: Loop Engineering & Agent SwarmsLearn how AI agents execute complex goals through iterative plan → act → observe → refine loops. Using tools such as Claude Code, Codex CLI, and LangGraph, explore goal-based execution, tool use, and continuous refinement through hands-on exercises. Learn how agent swarms differ from traditional multi-agent systems through dynamic task decomposition, delegation, parallel execution, and agent-to-agent coordination. Explore core swarm architectures, when they work best, and approaches.
- Al Agent Security, Guardrails & Production DeploymentGo where AI tutorials stop: protect, prove, ship, and operate production-ready agents. Learners attack and harden agents against real security threats, build automated evaluation and CI/CD quality gates, deploy to AWS and Azure, and implement observability and incident-response practices.
- Agentic Al Capstone ProjectChoose one of the industry-ready capstone projects based on your career goals. Build an AI portfolio website with a RAG chatbot that showcases your work, create a job assistance agent that finds roles and automates applications, or develop a production-ready agent harness from a product requirements document (PRD).
ELECTIVES
- Academic Masterclass Led by Columbia Engineering FacultyAttend a quarterly live masterclass led by Columbia Engineering faculty to explore emerging AI research, technologies, and industry developments, while gaining expert perspectives on evolving trends and real-world applications.
- Develop Al Agents on AzureLearn to build AI agents on Microsoft Azure, working with Azure-specific frameworks, deployment workflows, and security integration. You'll gain hands-on experience developing and hosting agents, with attention to reliability and compliance.
- Open Agent Orchestration with OpenClawGo beyond experimenting with agents and deploy your own AI assistant on a server you control. Learners connect OpenClaw to real-world channels and data, configure agent behavior and security, and build autonomous workflows that can run on scheduled triggers.
20+ Tools Covered
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Build Your AI Portfolio
Agent Sphere Enterprise Multi Agent AI Platform
AgentSphere uses multi-agent orchestration, MCP-based tools, guardrails, observability, and containerized deployment to build, govern, and operate enterprise AI workforces.
Skills learned
- Multi-Agent Orchestration
- Agent Governance
AI Portfolio with RAG Recruiter Chatbot
The AI Portfolio uses RAG, a recruiter chatbot, OpenClaw integration, guardrails, automated refresh, cost monitoring, and public deployment to answer recruiter questions.
Skills learned
- AI Application Deployment
- Conversational AI
Al Assistant Using an Agent Harness
The AI Assistant uses Azure OpenAI GPT-5 Mini, RAG, reusable skills, secure tools, consent-based memory, and guardrails to provide accurate and policy-compliant onboarding support.
Skills learned
- Agent Harness Development
- RAG
Building a Multi Agent Customer Support Assistant
The multi-agent assistant uses internal policy documents, RAG, and specialized agents to research accurate answers and generate policy-compliant customer replies.
Skills learned
- Multi-Agent Systems
- Agent Orchestration
Deploying a Secure OpenClaw Personal Assistant
The OpenClaw Personal Assistant uses secure configuration, Telegram integration, behavior guardrails, and scheduled automation to manage daily admin tasks and generate summaries.
Skills learned
- OpenClaw Deployment
- Workflow Automation
Deploying a Production Ready Customer Support Agent
The Customer Support Agent uses prompt-injection protection, evaluation workflows, containerization, and a secure deployment pipeline to deliver safer, production-ready support.
Skills learned
- AI Agent Security
- Cloud Deployment
Al Product Discovery Assistant
Develops an AI-powered Product Innovation and Design Studio that converts business problems into structured product strategies.
Skills learned
- Multi-Agent Orchestration
- Product Planning
Al Contract Clause Finder
The AI Contract Clause Finder helps legal, procurement, HR, and business teams identify, compare, explain, and assess clauses in contracts through natural language queries.
Skills learned
- Tool Calling & MCP
- LLM Guardrails
Program Advisor
Sean Wiggins
Executive Director, CVN, Columbia EngineeringAs a leader at CVN, Sean guides remote and hybrid curricular offerings, specializing in human-centered instructional design, faculty development, and teaching innovation. He collaborates with industry and academic partners to develop programs focused on emerging technologies.
Omesh Tickoo
Chief Data Scientist | Ex-Intel | PNNLOmesh leads AI systems strategy across GenAI, edge AI, and hardware acceleration, having delivered $100M+ in annual savings through AI-powered industrial defect detection. He also serves as an Adjunct Professor at Portland State University and holds 60+ patents and 60+ publications.
Program Trainers
Kaoutar El Maghraoui
24+ Years of ExperiencePrincipal Research Scientist
Thomas Plunkett
25+ Years of ExperienceSenior Principal Engineer
Lubina Zaidi PhD
16+ Years of ExperienceSenior Data Scientist
Donald High
23+ Years of ExperienceChief Data and Agentic Al Architect
Still have questions?
Our dedicated team is prepared to answer them.
Hear it from our Alumni
- LinkedIn profile of Terrance Johnson
Terrance Johnson
Principal SRE at MeridianLinkMy learning experience was very practical & engaging. The hands-on labs helped me understand how AI works in real applications. It also gave me exposure to Python & app dependencies, expanding my skills & showing me new possibilities for building tools beyond my current role. (Review for Simplilearn's Agentic AI curriculum)
- LinkedIn profile of Ravindar Gowrigari
Ravindar Gowrigari
Director at UBSThis program gave me the structure and clarity I was missing while working on AI agents. The hands-on learning and real-world projects helped me confidently build and deploy GenAI solutions that I now use for smarter data-driven decision-making in my work. (Review for Simplilearn's Agentic AI curriculum)
- LinkedIn profile of James D. Rodgers
James D. Rodgers
AI Integration Specialist at YMCA - AquaticsThe learning experience was practical & easy to follow. I gained hands-on skills in programming, LangChain, & AI that I could directly apply at work. The supportive instructors & real-world projects helped me build confidence & use GenAI skills for training, onboarding, & building useful AI tools. (Review for Simplilearn's Agentic AI curriculum)
Total Program Fee
Pay in Installments
You can pay monthly installments using our payment partners with low APR and no hidden fees.
Program Cohorts
- Limited seats Left
Columbia EEE Agentic AI Systems: Build, Deploy & Scale Program Nov 2026
14 Nov, 2026 - 20 Mar, 2027
WeekendSa
09:00 - 11:00 CST
Induction on 21 Oct, 2026
Who Is This Program For?
- Software Developers & Engineers
- Data Professionals
- Technical Product Managers
- Cloud & Solution Architects
Eligibility Criteria
- Be eager to build production-ready Agentic AI systems
- Have a fundamental understanding of Python
- Have 2+ years of experience in tech or data roles
How To Apply
- 1Submit Application
Complete the application by providing the essential details about yourself
- 2Reserve Your Seat
Secure your seat by completing the program fee payment
- 3Start 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 the U.S. markets.
Access to workshops, networking tools, and community support
Stay on top of your job hunt with a smart tracker and job board
Build an ATS-friendly resume using the AI Resume Builder
Practice anytime with the AI-powered Mock Interview Coach
Demand For Program
The first wave of Agentic Al was defined by possibility.
Today, companies are no longer asking, 'Can we build an AI agent?' They are asking, 'Can we trust it to operate inside the business?'
Agents are now expected to connect with data, APIs, applications, and critical workflows. Single-agent experiments evolved into multi-agent systems, agent loops, and intelligent architectures that can plan, coordinate, act, and learn from feedback. This evolution has brought new challenges. Failures are harder to trace, while security, observability, evaluation, and governance have become essential. Building a reliable agent in production requires a far deeper level of engineering.
The next phase of Agentic AI will be shaped by professionals who can move beyond prototypes and build systems that are secure, scalable, observable, and production-ready. This program prepares you to become one of them.
Demand For Program
Program FAQs
To ensure that money is not a barrier to learning, we offer various financing options to help make this program financially manageable. Please refer to our Admissions Fee and Financing section for more details.
About Columbia Engineering Executive Education
Columbia Engineering Executive Education offers customized online programs designed to upskill working professionals and help organizations achieve their strategic goals. The institution addresses the evolving demands of today’s technology landscape by preparing future engineering leaders and fostering technical expertise across industries.
Columbia Engineering Executive Education has partnered with Simplilearn to offer comprehensive online programs designed to equip learners with practical, industry-relevant skills. These programs combine Simplilearn’s award-winning learning model with applied pedagogy to create immediate career impact.