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Live Instructor-Led

Agentic AI Certification Training Program

Eduhubspot's Agentic AI Certification training gives end-to-end hands-on skill on Agentic AI solutions using industry-standard frameworks (LangChain, LangGraph, CrewAI) and orchestration tools (n8n) for diverse business use cases and to build autonomous AI agents.

Learn how to,
Implement production-ready multi-agent systems with specialized roles, agent-to-agent communication, and coordinated workflows for enterprise applications.
Deploy, monitor, and scale agentic AI systems to production environments with comprehensive testing, observability, cost optimization, and failure recovery mechanisms.
โญ 4.9+ Ratings (Trusted by 50,000 students)

Why Enroll for

Agentic AI Training?

Transform your career with practical Agentic AI and autonomous systems skills

AgenticAI market

The global Agentic AI market is experiencing explosive growth, expanding from roughly $5-$6 billion in 2024 to a projected $45-$57 billion by 2029-2031.

Job Opportunities

Agentic AI job opportunities are rapidly emerging across the globe, focusing on designing autonomous, LLM-powered agents for enterprise automation.

Industry Standard Curriculum

Gain maximum hands-on with frameworks like LangChain, LangGraph, AutoGen, and CrewAI.

Learn from AI Practitioners

Learn from top industry practitioners and architects with extensive expertise on building AI agents.

Hands-on Learning

Build confidence through hands-on practicals and real-world use cases with a final capstone project

Live Instructor Led classes

Attend live and interactive weekend classes led by senior Industry practitioners. Also get doubt clearing sessions

Career Assistance Services

Profile building, Interview preparation material, Mock Interviews - By Senior Experts

Global Certificate

Receive a globally accepted certificate to validate your learning and career advancement

Career

Benefits

for AI Agent & Autonomous Systems Roles

Director of Autonomous Systems โ€“ Leads the strategic vision, development, and deployment of enterpriseโ€‘grade autonomous AI agents. Drives crossโ€‘functional alignment and innovation at scale.

Hiring Companies

OpenAI
Microsoft
DeepMind

๐Ÿ“ˆ Market Outlook

44%โ€“46.3% CAGR (Projected)

Salary

โ‚น40 LPA
Min
โ‚น65 LPA
Average
โ‚น1.2 Cr
Max
Director of Autonomous Systems

AI Agent Operations Manager โ€“ Oversees the lifecycle of AI agents, ensuring reliability, performance, and continuous improvement. Bridges technical execution and business outcomes.

Hiring Companies

ServiceNow
DataRobot
BEAM
Microsoft

๐Ÿ“ˆ Market Outlook

44%โ€“46.3% CAGR (Projected)

Salary

โ‚น18 LPA
Min
โ‚น28.5 LPA
Average
โ‚น45 LPA
Max
AI Agent Operations Manager

Agent Integration Developer โ€“ Builds and integrates autonomous agent workflows, APIs, and orchestration layers. Implements agentic patterns and ensures seamless system interactions.

Hiring Companies

Salesforce
Anthropic
OpenAI

๐Ÿ“ˆ Market Outlook

44%โ€“46.3% CAGR (Projected)

Salary

โ‚น8.5 LPA
Min
โ‚น13.5 LPA
Average
โ‚น22 LPA
Max
Agent Integration Developer

Features

& Benefits

Participants will get all the below exclusive benefits through our Agentic AI Certification training

1
Live Interactive Classes

36 hours of Live classes

2
Practicals and Assignments

30+ Assignments to practice & Quizzes to reinforce concepts

3
Hands-on with real time projects

Hands-on Labs with real-world projects

4
Industry Leaders

Learn from Top Industry leaders

5
1:1 Doubt Clearing

1:1 Doubt-Clearing Sessions

6
Resume Building

Resume and LinkedIn Building

7
Career Assistance

Career Assistance Services

8
Capstone Project

Capstone Project to Design and Deploy Autonomous AI Agents

9
Certificate

Certificate of Completion

10
24/7 Support

24/7 Technical Support

11
Lifetime Access

Lifetime access to the course material

12
Career Mentoring

Career Mentoring sessions

Course

Curriculum

Module 1: Introduction to Agentic AI & AI Agents
Learning Outcomes:
  • Understand the evolution from traditional AI to Agentic AI
  • Define key concepts: agents, autonomy, goals, and environments
  • Differentiate between reactive and proactive agents
  • Set up the development environment for agentic workflows
Topics Covered:
  • What is Agentic AI vs traditional AI/ML
  • Agent architectures and types
  • Core components: perception, reasoning, action
  • Use cases across industries
  • Tool setup: Python, LangChain, OpenAI API
Module 2: LLM Reasoning & Context Management
Learning Outcomes:
  • Understand LLM capabilities and limitations for agentic workflows
  • Implement prompt engineering for agent behavior
  • Design ReAct (Reasoning + Acting) patterns
  • Manage context windows and token limits
Topics Covered:
  • LLMs as the brain of agents
  • Chain-of-Thought and ReAct framework
  • Conversation summarization and context pruning
  • Prompt engineering best practices
Module 3: Agent Memory & State Management
Learning Outcomes:
  • Implement short-term and long-term memory systems
  • Design conversation history management
  • Use vector databases for semantic memory
  • Manage agent state across sessions
Topics Covered:
  • Memory types: episodic, semantic, procedural
  • Vector stores: Pinecone, ChromaDB
  • Embeddings for retrieval
  • State persistence and token optimization
Module 4: Tool Integration, Structured Output & Validation
Learning Outcomes:
  • Connect agents to external tools and APIs
  • Implement function calling with structured outputs
  • Design tool selection logic
  • Validate and parse agent outputs reliably
Topics Covered:
  • OpenAI function calling and JSON mode
  • Pydantic-based validation
  • Tool schemas and API integrations
  • Error handling and parsing patterns
Module 5: Agent Planning & Task Decomposition
Learning Outcomes:
  • Implement planning algorithms
  • Design task decomposition strategies
  • Create goal-oriented agent behavior
  • Optimize planning for efficiency
Topics Covered:
  • Plan-and-Execute and ReWOO patterns
  • Sub-goal generation and tracking
  • Cost-aware planning decisions
  • Re-planning strategies
Module 6: Agentic Frameworks & Workflow Orchestration
Learning Outcomes:
  • Master LangChain and LangGraph for agent development
  • Use CrewAI for role-based collaboration
  • Implement workflow orchestration using n8n
  • Compare framework capabilities by use case
Topics Covered:
  • LangChain agents and chains
  • LangGraph cyclic workflows
  • CrewAI role-based agents
  • n8n visual orchestration
Module 7: RAG for Agents & Multi-modal Capabilities
Learning Outcomes:
  • Implement RAG pipelines for grounding
  • Design document ingestion and chunking strategies
  • Integrate vision/document understanding
  • Build multi-modal agentic systems
Topics Covered:
  • Retrieval strategies: similarity, MMR, hybrid
  • Embedding models and vector stores
  • Vision-enabled agents
  • PDF and image processing patterns
Module 8: Multi-Agent Systems: Architecture & Communication
Learning Outcomes:
  • Design multi-agent architectures
  • Implement communication protocols
  • Coordinate agent behaviors
  • Manage roles and responsibilities
Topics Covered:
  • Message passing and blackboard patterns
  • Hierarchical vs flat agent systems
  • Role assignment and specialization
  • Standardized message formats
Module 9: Advanced Patterns & Human-in-the-Loop
Learning Outcomes:
  • Implement supervisor-worker collaboration
  • Create human-in-the-loop workflows
  • Add reflection and critique loops
  • Build safe escalation paths
Topics Covered:
  • Collaborative decision-making patterns
  • Approval workflows and handoff
  • Human feedback integration
  • Task routing and delegation
Module 10: Testing, Evaluation & Monitoring
Learning Outcomes:
  • Design comprehensive testing strategies
  • Implement evaluation metrics and benchmarks
  • Monitor behavior in production
  • Debug and troubleshoot workflows
Topics Covered:
  • Unit and integration testing for agents
  • LangSmith/LangFuse tracing
  • Performance and cost benchmarks
  • A/B and regression testing
Module 11: Production Deployment, Resilience & Cost Optimization
Learning Outcomes:
  • Deploy agents to production environments
  • Implement resilience and failure recovery
  • Design scalable, reliable systems
  • Optimize costs and performance
Topics Covered:
  • FastAPI/Flask deployment patterns
  • Docker and cloud deployment basics
  • Circuit breakers, retries, graceful degradation
  • Caching, model routing, quota management
Module 12: Security, Adversarial Testing & Capstone Project
Learning Outcomes:
  • Implement comprehensive security controls
  • Conduct adversarial testing and red teaming
  • Address ethics and safety in agentic AI
  • Build an end-to-end production-ready capstone
Topics Covered:
  • Prompt injection and jailbreaking prevention
  • Input/output guardrails and sanitization
  • Compliance and data-retention basics
  • Capstone: multi-agent system with HITL + monitoring
Download Curriculum

Tools you will learn during th

Training

Projects

What Your Certificate Will

Look Like

A customised certificate from EduHubSpot on the successful completion of Agentic AI Certification Training Program.

Certification awarded to Shrasti Patel for earning 30 PDUs by completing the Artificial Intelligence Project Management Certification course from Oct 05, 2024 to Oct 13, 2024, issued by Certification Education Providers Private Limited with signature of course advisor Gautham Sudakar.

Past Participant

Testimonials

Hear from professionals who turned their PMPยฎ training into promotions, pay raises, and dream roles โ€” and know that you can be next.

Featured In Leading

Publications

Career Assistance

Services

Webinar
Live Sessions

Career Assistance Services

Resume Preparation

Craft ATS Job-Ready resumes through Expert Asisstance.

1.5 Building a LinkedIn Profile

Interview Questions consolidated for an Hassle Free Interview Prep.

Materials for Interview Prep

Self-Branding through best Linkedin Profile.

Career Counselling

Know where you stand today in Terms of Skills and Technology

Frequently Asked

Questions

Common questions about our Agentic AI Certification Training Program.

Do I need coding knowledge to create AI agents?

Basic Python programming knowledge will be beneficial. However, we offer Python programming fundamentals as complimentary as part of the course contents.

Is advanced coding involved in Agentic AI course?

No. In the course we use low-code and fair-code frameworks like n8n and CrewAI. Basic Python programming knowledge is the requirement.

How can I work on the practicals?

We will help you set up the required environments for practicals. Google Colab and an OpenAI API key are required.

How long is the course, and how long can I access the material?

Course duration is 2 months, including project work. Participants will get lifetime access to the course material.

Who are the instructors?

Our instructors are senior industry practitioners with real-time experience in the technologies they teach.

What if I miss any class?

All live classes are recorded and auto-added to your LMS. You can cover missed lectures through recordings.

How recognised is your certificate?

Eduhubspot's certification courses are designed in collaboration with industry experts and adhere to global standards. The course completion certificate you earn is highly regarded by major organizations, giving you a competitive edge in the job market.

What placement assistance will I get from the training?

Once the final project is completed, we help all participants with profile building, interview preparation, and mock interviews.

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