Does this Agentic AI Systems: Build, Deploy & Scale program offer any financial aid?

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.

Why is Agentic AI becoming an important skill now?

The first wave of Agentic AI focused on proving what was possible. Today, the focus is shifting from prototypes to AI agents that can work reliably in production environments.

How has Agentic AI evolved beyond prototypes?

Early agents could reason, use tools, and complete individual tasks. Today’s systems increasingly connect with data, APIs, and applications while using multi-agent architectures and agent loops to plan, coordinate, act, and improve through feedback.

Why is production-ready Agentic AI harder to build?

As agents become more autonomous and interconnected, failures become harder to trace. Security, evaluation, observability, governance, and reliability become critical engineering considerations.

What skills are becoming important for Agentic AI professionals?

Professionals increasingly need to move beyond building demos and learn how to design, orchestrate, evaluate, secure, deploy, and monitor Agentic AI systems.

How does this program prepare me for this shift?

The program helps you build the engineering skills needed to take Agentic AI from prototype to production-ready systems that are reliable, secure, observable, and ready for real-world use.

How do learner reviews help me?

Learner reviews give you a broader view of the learning experience of the AI programs at Simplilearn, including feedback on live classes, instructors, hands-on projects, support, and career-focused outcomes. They help you understand what learners value most across their learning journeys.

Agentic AI Systems: Build, Deploy & Scale

Industry Partner:

4.5 Rated

200+ Learners

Application closes on
20 Oct, 2026
Program Duration
8 weeks (7–8 hrs/week)
Learning Format
Live, Online, Interactive

Why Join this Program

Prestigious Credentials
Earn a program completion certificate from Columbia Engineering Executive Education and Simplilearn

Earn a program completion certificate from Columbia Engineering Executive Education and Simplilearn
Build Production-Ready Al
Master end-to-end Agentic Al lifecycle - foundations, engineering, orchestration & deployment
Applied Hands-On Learning
Learn through 8+ hands-on projects, using 20+ AI tools and frameworks
Guided by Global Practitioners
Learn from Subject Matter Experts (SMEs) with experience at leading global organizations

Corporate Training

Enroll your employees into this program, NOW!

Talk to Our Advisor

Program Overview

Everyone built AI agents in 2025. In 2026, the challenge is understanding why these systems fail in production and building secure, scalable ones that don't. This program prepares you to turn prototypes into production-ready solutions.

Key Features

Understand how AI evolves into intelligent agents and master the complete agent lifecycle
Design, build, orchestrate & deploy production-ready agentic AI systems
Develop intelligent agentic AI systems with Harness Engineering, Loop Engineering & Agent Swarms
Deploy and operate your own autonomous AI agent on a live server
Create layered guardrails and defend agents against prompt injection and unsafe actions
Evaluate agent quality and safety, and deploy reliable, production-ready AI systems
Design and orchestrate multi-agent workflows that plan and collaborate reliably
Master Harness Engineering to reliably build production-ready AI agents
Attend a quarterly live masterclass led by Columbia Engineering faculty on emerging industry trends, at no additional cost
Gain hands-on experience with 20+ Agentic AI tools, frameworks, and cloud platforms
Build practical skills through 8+ hands-on projects including a capstone
Simplilearn Career Service helps you get noticed by top hiring companies

Program Advantage

Learn to build production-ready Agentic AI systems with Columbia Engineering Executive Education, delivered by Simplilearn, and unlock new opportunities in the rapidly evolving Agentic AI landscape.

A Hallmark of Excellence
Program Completion Certificate
- Build a showcase-ready Agentic AI portfolio by completion
- Gain confidence to design and deploy production-ready AI agents
Gain an Industry Edge
Microsoft Learn Certificate
- Gain exposure to the Azure AI services ecosystem
- Earn a certificate hosted on the Microsoft Learn portal

Program Details

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.

Learning Path

Program On-Boarding
- Introduction to the program structure and curriculum
- Overview of the learning journey and expected outcomes
- Understanding the support system available to learners
- Key concepts and skills covered throughout the program
Getting Started with Agentic AI
- Get an overview of the program and learning journey
- Review the Terms & Conditions
- Understand the weekly flow and full program schedule
- Access other essential information and resources to help you get started smoothly
Building Blocks of Agentic AI
- Understand the evolution from AI and ML to Agentic AI
- Explore Transformers, LLMs, reasoning models, and attention mechanisms
- Understand how ReAct, CoT, and Reflection enable agentic behavior
- Map the 4-layer GenAI technology stack and agent architecture
- Explore the AI Agent Lifecycle from requirements to deployment and monitoring
Prompt Engineering & the Internals of Learning Algorithms
- Master prompt engineering techniques to get better, more reliable AI outputs
- Understand how learning algorithms work and how AI systems learn from data
- Apply this knowledge to interact with AI more effectively and optimize results
Workshop: Al Agents in Action
- Build AI-powered workflows in n8n using triggers, actions, app integrations, data mapping, and AI nodes
- Apply these skills through hands-on projects across sales, product feedback, and e-commerce
Generative Al Applications & Agents
- Understand LLMs, VLMs, multimodal models, and model limitations
- Work with function calling and MCP tools
- Build and evaluate a complete RAG pipeline
- Benchmark models for context, hallucination, latency, and cost
- Deploy an AI product using Gradio and Hugging Face Spaces
Programming with OpenAl
- Build Generative AI applications using OpenAI APIs and LLMs
- Analyze data and develop AI workflows with LangChain
- Work with multimodal AI across image, audio, and video
Designing Multi-Agent Al Systems
- Design engineering-grade multi-agent architectures
- Build Agentic RAG and collaborative agent workflows
- Implement supervisor, handoff, and swarm orchestration
- Apply the A2A protocol for agent-to-agent communication
- Manage failures, retries, latency, and accuracy trade-offs
Architect Modern Al Agents with Harness Engineering
- Understand Harness Engineering and the runtime around an LLM
- Design prompt, context, memory, tool, skill, and evaluation layers
- Control agent behavior through policy and instruction files
- Implement model routing, tool approvals, audit trails, and security
- Build self-improving harnesses through evaluation and continuous iteration
Preview
Workshop: Loop Engineering & Agent Swarms
- Understand how iterative agent loops enable autonomous task execution
- Build and experiment with agent workflows using Claude Code, Codex CLI, and LangGraph
- Apply loop-based execution to solve complex, multi-step tasks
- Understand the architecture and coordination patterns behind agent swarms
- Explore dynamic task decomposition, delegation, and parallel execution
- Examine swarm-based approaches such as Kimi Agent Swarm and their applications
Al Agent Security, Guardrails & Production Deployment
- Implement input, output, and tool-use guardrails
- Protect agents against prompt injection, jailbreaks, and tool abuse
- Evaluate agents using RAGAS, golden test sets, and regression testing
- Containerize and deploy agents using FastAPI, Docker, AWS, and Azure
- Implement observability, CI/CD, tracing, and incident response
Agentic Al Capstone Project
- Choose one capstone project
- Build an end-to-end Agentic AI application
- Deploy a production-ready portfolio project
- Showcase your engineering skills to employers

Electives:

Academic Masterclass Led by Columbia Engineering Faculty
- Attend a quarterly live masterclass led by Columbia Engineering Faculty
- Explore emerging AI research, technologies, and industry developments
- Gain faculty perspectives on evolving AI trends and applications
Develop Al Agents on Azure
- Build AI agents on Microsoft Azure
- Deploy secure AI Agent applications
- Follow production-ready cloud workflows
Open Agent Orchestration with OpenClaw
- Deploy a personal AI agent on a VPS
- Configure agent behavior using AGENTS.md, SOUL.md, and USER.md
- Connect agents with Telegram, Gmail, Calendar, and Drive
- Configure approval rules, trust boundaries, and security controls
- Build scheduled workflows using cron jobs and heartbeat routines

Programme Syllabus

16+ Skills Covered

Agentic Al Engineering
Harness Engineering
Agent Swarm Design
Agentic RAG
Al Agent Evaluation
Al Observability
Cloud Al Deployment
Loop Engineering
Model Context Protocol
Al Governance
Production Al Operations
Multi Agent Orchestration
Al Guardrail Implementation
Al Workflow Automation
Agentic Al Architecture
Agent Memory Management

20+ Tools Covered

Build Your AI Portfolio

Project 1
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.
Project 2
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.
Project 3
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.
Project 4
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.
Project 5
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.
Project 6
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.
Project 7
Al Product Discovery Assistant
Develops an AI-powered Product Innovation and Design Studio that converts business problems into structured product strategies.
Project 8
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.

Disclaimer - The projects have been built leveraging real publicly available datasets from organizations.

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An Immersive Learning Experience

Peer to Peer engagement

Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.

Flexi Learn

Missed a class? Access recordings to always maintain learning progress and keep up with your cohort.

Mentoring session(s)

Expert guidance sessions from mentors for doubt clarifications, project assistance, and learning support.

Learning Support

Get a dedicated Cohort Manager for all your queries and help you succeed at every learning step.

Peer to Peer engagement

Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.

Flexi Learn

Mentoring session(s)

Learning Support

Program Advisors and Trainers

Program Advisors

Omesh Tickoo
Chief Data Scientist | Ex-Intel | PNNL
Omesh 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.
Sean Wiggins
Executive Director of Columbia Video Network
As 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.

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Program Trainers

Dr Kaoutar El Maghraoui
24+ Years of Experience
Adjunct Professor, Columbia University I IBM
Donald High
23+ Years of Experience
Principal Agentic Al Architect I Ex-Walmart
Thomas Plunkett
25+ Years of Experience
Senior Principal Engineer I Ex-Oracle

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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

Join the Agentic AI Revolution

Agentic AI is evolving from prototypes to production systems, making security, observability, evaluation, and governance essential. The future belongs to professionals who can build secure, dependable, production-ready Agentic AI systems

AI agents became the fastest-growing AI skill in U.S. labor-market analysis

Source: LinkedIn Econ. Graph

40%

Enterprise applications expected to embed AI agents by 2026

Source: Gartner

280% YoY

Agentic AI skill mentions in job postings grew by 280%+ in 2025.

Source: Lightcast

Unlock Your Next AI Role

Batch Profile

This program caters to working professionals from a variety of industries and backgrounds; the diversity of our students adds richness to class discussions and interactions.

Industry
The class consists of learners from excellent organizations and diverse industries
Where Learners Come From
Information Technology - 45%BFSI - 13%Healthcare - 6%Manufacturing - 5%Public Sector - 7%Others - 24%
Companies

Learner Reviews

Admission Details

Application Process

The application process consists of three simple steps. An offer of admission will be made to the selected candidates and accepted by the candidates by paying the admission fee.

STEP 1

Submit Application

Complete the application by providing the essential details about yourself

STEP 2

Reserve Your Seat

Secure your seat by completing the program fee payment

STEP 3

Start Learning

Begin your learning journey on the designated cohort start date

Eligibility Criteria

For admission to the Agentic AI Systems: Build, Deploy & Scale, candidates should:

Have a strong eagerness to build production-ready Agentic Al systems

Have a fundamental understanding of Python

Have 2+ years of experience in tech or data roles

Admission Fee & Financing

The admission fee for this program is $2,690

Financing Options

We are dedicated to making our programs accessible. We are committed to helping you find a way to budget for this program and offer a variety of financing options to make it more economical.

Total Program Fee

$2,690

Pay In Installments, as low as

$269/month

You can pay monthly installments using our payment partners with low APR and no hidden fees.

Admission Closes on :

Apply now

Apply Now

Program Benefits

Master the complete Agentic Al lifecycle
Learn Harness Engineering, Agent Loops, and Agent Swarms
Applied Learning through 8+ projects including a capstone
Get exposure to 20+ tools & frameworks
Gain confidence to build production-ready Agentic AI systems

Program Cohorts

Next Cohort

Columbia EEE Agentic AI Program Nov 2026
- Date
  Time
  Batch Type
- Program Induction
  21 Oct, 2026
  10:00 CDT
- Regular Classes
  5 Oct, 2026 - 15 Feb, 2027
  09:00 - 13:00 CDT
  WeekendSaSu
- Apply Now

Got Questions Regarding Cohort Dates?

FAQs

Does this Agentic AI Systems: Build, Deploy & Scale program offer any financial aid?
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.
Why is Agentic AI becoming an important skill now?
The first wave of Agentic AI focused on proving what was possible. Today, the focus is shifting from prototypes to AI agents that can work reliably in production environments.
How has Agentic AI evolved beyond prototypes?
Early agents could reason, use tools, and complete individual tasks. Today’s systems increasingly connect with data, APIs, and applications while using multi-agent architectures and agent loops to plan, coordinate, act, and improve through feedback.
Why is production-ready Agentic AI harder to build?
As agents become more autonomous and interconnected, failures become harder to trace. Security, evaluation, observability, governance, and reliability become critical engineering considerations.
What skills are becoming important for Agentic AI professionals?
Professionals increasingly need to move beyond building demos and learn how to design, orchestrate, evaluate, secure, deploy, and monitor Agentic AI systems.
How does this program prepare me for this shift?
The program helps you build the engineering skills needed to take Agentic AI from prototype to production-ready systems that are reliable, secure, observable, and ready for real-world use.
How do learner reviews help me?
Learner reviews give you a broader view of the learning experience of the AI programs at Simplilearn, including feedback on live classes, instructors, hands-on projects, support, and career-focused outcomes. They help you understand what learners value most across their learning journeys.