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Agentic AI Certification Training Course
Agentic AI Certification Training Course
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Live Online Classes starting on 7th Jun 2025
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24,999
Starts at 8,333 / monthWith No Cost EMI Know more
Why enroll for Agentic AI Training Course ?
AI Agents Training Course Benefits
The Agentic AI market is anticipated to grow at a CAGR of 45.8% from 2025 to 2030, with 90% of businesses anticipating it to be crucial to their future success. As businesses adopt Agentic AI, the demand for experts in autonomous AI systems is soaring. Our program empowers you with cutting-edge expertise to thrive in this rapidly evolving field at the forefront of AI innovation.
Annual Salary
Hiring Companies
Want to become a AI Research Scientist?
Annual Salary
Hiring Companies
Want to become a AI Research Scientist?
Annual Salary
Hiring Companies
Want to become a AI Research Scientist?
Annual Salary
Hiring Companies
Want to become a AI Research Scientist?
Why Agentic AI Training Course from edureka
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
Lifetime Access
- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
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About your Agentic AI Training Course
Skills Covered in this AI Agents online Course
Agentic AI Tools Covered
Agentic AI Training Course Curriculum
Curriculum Designed by Experts
Agentic AI Essentials
11 Topics
Topics
- Agentic AI Introduction
- AI Agents vs. Agentic AI
- Comparison: Agentic AI, Generative AI, and Traditional AI
- Agentic AI Building Blocks
- Autonomous Agents
- Human in the Loops Systems
- Single and Multi Agent AI Systems
- Agentic AI Frameworks Overview
- Ethical and Responsible AI
- Agentic AI Best Practices
- AI Implementation Success Stories: Case Studies
![skill]( "Hands On Experience")
- Analyzing AI Agent Use Cases
- Exploring Agentic AI Frameworks
![skill]( "skill you will learn")
- Understanding Agentic AI Concepts
- Identifying AI Agent Capabilities and Limitations
- Navigating AI Frameworks and Architectures
- Ethical and Responsible AI
Agentic AI: Architectures and Design Patterns
12 Topics
Topics
- Agentic AI Architecture
- Agentic Architecture Types
- Key Components of the Agentic AI Framework
- Perception Module
- Cognitive Module
- Action Module
- Learning Module
- Collaboration Module
- Security Module
- Agentic AI Design Patterns
- Reflection Pattern
- Tool Use Pattern
- Planning Pattern
- ReAct (Reasoning and Acting) and ReWOO (Reasoning with Open Ontology)
- Multi Agent Pattern
- Design Considerations
![skill]( "Hands On Experience")
- Designing an AI agent architecture
- Implementing different agentic AI design patterns
![skill]( "skill you will learn")
- Understanding Agentic AI Frameworks
- Implementing AI Design Patterns
- Designing Secure and Scalable AI Architectures
Working with LangChain and LCEL
10 Topics
Topics
- Components and Modules
- Data Ingestion and Document Loaders
- Text Splitting
- Embeddings
- Integration with Vector Databases
- Introduction to Langchain Expression Language (LCEL)
- Runnables
- Chains
- Building and Deploying with LCEL
- Deployment with Langserve
![skill]( "Hands On Experience")
- Build a Resume Screening Application with LangChain
- Develop a Legal Document Review Application with LangChain
![skill]( "skill you will learn")
- Data Processing with Langchain
- AI-Powered Document Retrieval
- Building AI Pipelines with LCEL
Building AI Agents with LangGraph
13 Topics
Topics
- Introduction to LangGraph
- State and Memory
- State Schema
- State Reducer
- Multiple Schemas
- Trim and Filter Messages
- Memory and External Memory
- UX and Human-in-the-Loop (HITL)
- Building Agent with LangGraph
- Long Term Memory
- Short vs. Long Term Memory
- Memory Schema
- Deployment
![skill]( "Hands On Experience")
- Building a Finance Bot with LangGraph
![skill]( "skill you will learn")
- State Management in AI Agents
- Implementing Long-Term AI Memory
- Deploying AI Agents with LangGraph
Implementing Agentic RAG
8 Topics
Topics
- What is Agentic RAG?
- Agentic RAG vs. Traditional RAG
- Agentic RAG Architecture and Components
- Understanding Adaptive RAG
- Variants of Agentic RAG
- Applications of Agentic RAG
- Agentic RAG with Llamaindex
- Agentic RAG with Cohere
![skill]( "Hands On Experience")
- Create an AI-Powered Sales Report Analyzer with LlamaIndex
- Create a Market Research Agent with RAG & Cohere
![skill]( "skill you will learn")
- Implementing RAG Techniques
- Building AI Agents with LlamaIndex and Cohere
- Optimizing AI Retrieval Systems
Developing AI Agents with Phidata
10 Topics
Topics
- Agents
- Models
- Tools
- Knowledge
- Chunking
- Vector DB
- Storage
- Embeddings
- Workflows
- Developing Agents with Phidata
![skill]( "Hands On Experience")
- Design a Data Analysis Agent with Phidata
![skill]( "skill you will learn")
- Building AI Agents with Phidata
- Optimizing AI Workflows
Multi Agent Systems with LangGraph and CrewAI
9 Topics
Topics
- Multi Agent Systems
- Multi Agent Workflows
- Collaborative Multi Agents
- Multi Agent Designs
- Multi Agent Workflow with LangGraph
- CrewAI Introduction
- CrewAI Components
- Setting up CrewAI environment
- Building Agents with CrewAI
![skill]( "Hands On Experience")
- Building Multi Agent Systems with LangGraph and CrewAI
![skill]( "skill you will learn")
- Build a Customer Support Chatbot with LangGraph
- Design a Stock Analysis Agent with CrewAI
Advanced Agent Development with Autogen
10 Topics
Topics
- Autogen Introduction
- Salient Features
- Roles and Conversations
- Chat Terminations
- Human-in-the-Loop
- Code Executor
- Tool Use
- Conversation Patterns
- Developing Autogen-powered Agents
- Deployment and Monitoring
![skill]( "Hands On Experience")
- Develop an AI Research Agent with Autogen
![skill]( "skill you will learn")
- Building Adaptive AI Agents
- Deploying AI Agents with Autogen
AI Agent Observability and AgentOPs
10 Topics
Topics
- AI Agent Observability and AgentOPs
- Langfuse Dashboard
- Tracing
- Evaluation
- Managing Prompts
- Experimentation
- AI Observability with Langsmith
- Setting up Langsmith
- Managing Workflows with Langsmith
- AgentOps Practical Implementation
![skill]( "Hands On Experience")
- AI Observability with Langsmith
- AgentOps Practical Implementation
![skill]( "skill you will learn")
- Monitoring AI Agent Performance
- Managing AI Workflows
- Implementing AI Experimentation and Observability
Building AI Agents with No/Low- Code Tools
12 Topics
Topics
- Introduction to No-Code/Low-Code AI
- Benefits and Challenges of No-Code AI Development
- Key Components of No-Code AI Platforms
- Building AI Workflows Without Coding
- Designing AI Agents with Drag-and-Drop Interfaces
- Integrating No-Code AI with Existing Systems
- Customizing and Fine-Tuning AI Solutions
- Optimizing Performance and Efficiency in No-Code AI
- Security and Compliance Considerations in No-Code AI
- Best Practices for Deploying No-Code AI Solutions
- Real-World Use Cases and Applications of No-Code AI
- Scaling and Future Trends in No-Code AI
![skill]( "Hands On Experience")
- Scaling and Future Trends in No-Code AI
- Design Your own SEO Agent with Relevance AI
- Creating an AI Agent with Langflow
![skill]( "skill you will learn")
- No-Code AI Development
- Workflow Automation Using AI
- Building and Deploying AI Agents
Bonus Module: Generative and Agentic AI on Cloud (Self-paced)
12 Topics
Topics
- Deploying Generative AI Models with Amazon Bedrock
- Implementing Retrieval-Augmented Generation (RAG)
- Building and Managing AI Agents
- Serverless AI Agent Deployment
- Observability and Monitoring AI Agents
- Developing Generative AI Applications with Azure OpenAI Service
- Implementing Agentic AI Workflows with Azure Machine Learning (AML)
- Fine-Tuning Large Language Models (LLMs) on Azure
- Building AI Agents on Azure
- AI Model Deployment and Governance on Azure
- Working with Vertex AI Agent Builder
- Building No Code Conversational AI Agents
![skill]( "Hands On Experience")
- Build and Deploy AI Models on AWS Bedrock, Azure OpenAI, and GCP Vertex AI
![skill]( "skill you will learn")
- Cloud-based AI Model Deployment of Generative AI Models
- AI Agent Development on Cloud
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Agentic AI Course Description
Agentic AI Training Course Overview and Key Features
The Agentic AI course enables learners to build autonomous AI agents using LLMs like GPT without coding. This course by Edureka offers hands-on projects and tools like LangChain, CrewAI, and AutoGen. It covers essential concepts of agentic AI, agentic AI design patterns and architecture, agentic RAG, building AI agents with different frameworks, AI observability and monitoring, and using no/low code tools for building agents.
Key Features
- No-code AI agent development
- Real-world LLM projects
- Tools: LangChain, AutoGen, CrewAI
- Capstone project with expert guidance
- Lifetime access and career support
What are the prerequisites for this Agentic AI Training Course?
Basic Python, ML, DL, NLP, generative AI, and prompt engineering knowledge is needed. Refresher materials are provided before live sessions.
What will participants learn during this Course?
Upon completing the Agentic AI course, participants will learn:
- Build autonomous AI agents with LangChain, LangGraph, and CrewAI.
- Implement agentic RAG for smart retrieval.
- Develop multi-agent AI systems.
- Integrate Autogen for adaptive workflows.
- Monitor AI with LangFuse observability.
- Use no-code AI development tools.
- Deploy on AWS, Azure, and GCP.
- Complete hands-on projects for real-world skills.
Who should take this AI Agents Training Course?
The course is ideal for:
- AI Enthusiasts and Developers
- LLM Engineers & Generative AI Engineers
- AI Research Scientists
- AI/ML Practitioners
- Freshers looking to enter AI roles
- Professionals aiming to use Agentic AI for automation, reasoning, and decision-making
What is the Cost of this Course?
Edureka offers Agentic AI Course at a very affordable cost of ₹24,999 with EMI options starting at ₹8,333 per month and offers discounts, with both weekday and weekend batches available.
How long does it take to complete this course?
The Agentic AI Certification Course by Edureka takes approximately 5 weeks to complete.
Classes are held on weekends (Saturdays and Sundays). Includes live instructor-led sessions for interactive learning. Offers a bonus self-paced module on Generative and Agentic AI on Cloud with 12 topics. The self-paced module lets learners explore advanced concepts at their own convenience.As AI grows more independent, understanding its ethical and safety implications becomes crucial, making expertise in this field highly valuable for the future.
Projects
Build a Self-correcting Coding Assistant with LangChain
Develop a coding assistant using LangChain that identifies and corrects errors in code snippets automatically. Implement AI-driven error detection and self-correction to enhance ....Building a Finance Bot with LangGraph
Create an AI-powered finance assistant that provides real-time financial insights and recommendations using LangGraph.Build a Resume Screening Application with LangChain
Develop an AI-powered resume screening tool that extracts and ranks key candidate information using LangChain components.Create an AI-Powered Sales Report Analyzer with LlamaIndex
Build an AI tool that analyzes sales reports, extracts key insights, and generates summaries using LlamaIndex.Design a Data Analysis Agent with Phidata
Build an AI-powered data analysis agent using Phidata to process and visualize structured and unstructured data.Build a Customer Support Chatbot with LangGraph
Design and deploy a multi-agent chatbot for customer support using LangGraph to handle multiple inquiries efficiently.Design a Stock Analysis Agent with CrewAI
Develop an AI agent that analyzes stock trends, retrieves financial news, and provides investment insights using CrewAI.Develop an AI Research Agent with Autogen
Create an AI agent that autonomously researches topics, synthesizes information, and generates structured reports using Autogen.Design Your Own SEO Agent with Relevance AI
Create an SEO-optimized content generator using Relevance AI that analyzes keywords and suggests improvements.Content Writer Agent in Wordware
Create an SEO-optimized content generator using Relevance AI that analyzes keywords and suggests improvements.Agentic AI Certification
Upon successful completion of the AI agents training, Edureka provides the course completion certificate, which is valid for a lifetime.
To unlock Edureka’s agentic AI course completion certificate, you must ensure the following:
Fully participate in the agentic AI Course and complete all modules.
Complete the quizzes and hands-on projects listed in the curriculum.
Earning an Agentic AI certification offers multiple career and industry benefits, including:
Validates skills in building autonomous AI agents with LangChain and LangGraph.
Boosts career opportunities in AI and automation.
Relevant for finance, healthcare, and robotics industries.
Gives a competitive job market edge.
Highlights ethical and responsible AI development.
After earning the Certification, you can pursue roles such as
AI/ML Engineer
AI Research Scientist
Generative AI Engineer
LLM Engineer
AI Agent Engineer
Autonomous Systems Developer
and AI Solutions Architect
This certification enhances career growth in AI development, automation, and intelligent decision-making systems.
Agentic AI certification can be challenging as it requires a solid understanding of AI principles, autonomous systems, and AI agent frameworks like LangChain and LangGraph. However, with dedication, hands-on practice, and structured learning, it is achievable. Enrolling in an agentic AI course with hands-on projects and expert guidance can significantly enhance your preparation and mastery of AI agent development.
John Doe
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The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate
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Frequently Asked Questions (FAQs)
What is Agentic AI?
Agentic AI refers to artificial intelligence systems that can autonomously make decisions, take actions, and pursue goals with minimal human intervention. Unlike traditional AI, which adheres to predetermined rules, agentic AI may dynamically adapt to new situations. It is widely utilized in robotics, virtual assistants, self-driving cars, and sophisticated decision-making processes.
Why learn Agentic AI?
Learning Agentic AI is essential for:
Enables smart, adaptive autonomous systems
Advances in robotics and automation
Creates AI career opportunities
Raises awareness of AI ethics and safety
Prepares for the future of AI technology
What if I miss a live class of this course?
You will have access to recorded sessions that you can review at your convenience.
What if I have questions after completing this online training?
You can reach out to Edureka’s support team for any queries, and you’ll have access to the community forums for ongoing help.
What would be my role as an agentic AI Engineer?
As an agentic AI Engineer, you'll be responsible for
Design AI agents that perceive, decide, and act to meet goals
Use reinforcement learning, NLP, and planning techniques
Build autonomous agents that adapt to change
How soon after signing up would I get access to the learning content?
Once you sign up, you will get immediate access to the course materials and resources.
What are the features of agentic AI?
The key features of agentic AI are:
- Autonomy: Operates independently with minimal human intervention
- Perception: Senses and understands its environment
- Decision-making: Makes intelligent choices based on data and goals
- Adaptability: Learns and adjusts to changing conditions
- Goal-oriented: Focuses actions on achieving specific objectives
- Learning: Uses techniques like reinforcement learning to improve over time
- Planning: Anticipates future states and strategizes accordingly
Is ChatGPT, Gemini, Claude, or Deepseek an example of agentic AI?
No, ChatGPT, Gemini, Claude, and Deepseek are not fully agentic AI on their own. They are large language models (LLMs) designed for generative AI tasks like text generation, summarization, and answering questions.
However, when integrated with agentic AI frameworks like LangChain, AutoGen, or CrewAI, these models can exhibit agent-like behavior by performing autonomous tasks, using tools, and making goal-driven decisions.
How does the agentic AI online course contribute to career advancement in the AI field?
The agentic AI course enhances career advancement by
Enhance career advancement with specialized skills
Boosts professional credibility
Opens doors to high-demand AI roles
Expands career prospects in AI
Keeps professionals updated with AI advancements
Certification is a key asset for standing out in a competitive field
Supports long-term career growth
Can someone with minimal AI experience pursue the agentic AI course and find related job opportunities?
Yes, individuals with minimal AI experience can pursue the agentic AI online training, especially if they have a basic understanding of AI concepts and programming fundamentals. Prior experience with Python, AI workflows, and cloud platforms can be beneficial.
This certification helps professionals build expertise in AI agent development, autonomous systems, and multi-agent collaboration, unlocking career opportunities in roles such as LLM Engineer, Generative AI Engineer, AI Research scientists, and AI/ML practitioners. Having skills in emerging technologies like Autonomous AI Agents can further impact salary growth and job opportunities in this field.
Is it worth learning Agentic AI?
Yes, learning Agentic AI is likely worth it, as a rapidly growing field with significant potential to revolutionise how businesses operate by automating complex tasks, enabling autonomous decision-making, and facilitating seamless human-AI collaboration, it is regarded as a valuable skill for the future of work across a wide range of industries.
Why should you become an Agentic AI Engineer?
Becoming an agentic AI engineer is beneficial for the participant as it is transforming the business operations, enhancing productivity, and redefining innovation.
Is AI Agent Engineer a good Career Option?
Yes, becoming an AI Agent Engineer is a very promising career path due to the rapidly growing field of agentic AI, which is viewed as a significant technological advancement with enormous potential across industries, making it a high-demand area for skilled professionals with the ability to build and deploy autonomous AI systems.
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