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Agentic AI for Developers Certification Training

Agentic AI for Developers Certification Training
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    Instructor-led Agentic AI for Developers live online Training Schedule

    Flexible batches for you

    Why enroll for Agentic AI for Developers?

    pay scale by Edureka courseThe Agentic AI Market, valued at USD 7.28 billion in 2025, is projected to reach USD 41.32 billion by 2030 - Mordor Intelligence
    Industries75% of consumers prefer businesses using Agentic AI for personalization, boosting customer retention by 40% - Market.us
    Average Salary growth by Edureka courseThe average annual salary for an AI Agent Engineer in the US is US$121,000 with an average annual bonus of $28,730 - Glassdoor

    AI Agents Training Course Benefits

    Annual Salary
    AI Research Scientist average salary
    Hiring Companies
     Hiring Companies
    Annual Salary
    LLM Engineer average salary
    Hiring Companies
     Hiring Companies
    Annual Salary
    Generative AI Engineer average salary
    Hiring Companies
     Hiring Companies
    Annual Salary
    AI Agent Engineer average salary
    Hiring Companies
     Hiring Companies

    Why Agentic AI for Developers from edureka

    Live Interactive Learning

    Live Interactive Learning

    • World-Class Instructors
    • Expert-Led Mentoring Sessions
    • Instant doubt clearing
    Hands-On Project Based Learning

    Hands-On Project Based Learning

    • Industry-Relevant Projects
    • Course Demo Dataset & Files
    • Quizzes & Assignments
    Industry Recognised Certification

    Industry Recognised Certification

    • Edureka Training Certificate
    • Graded Performance Certificate
    • Certificate of Completion

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    About your Agentic AI for Developers

    Skills Covered in this AI Agents online Course

    • skillAgentic AI Development
    • skillAI Architecture Design
    • skillAgentic RAG Implementation
    • skillMulti-agent Systems
    • skillAI Observability & Ops
    • skillBuilding No/ Low Code AI Agents

    Agentic AI Tools Covered

    • python
    • Visual-code-studio
    • colab
    • Langchain
    • PHI-data
    • Crewai
    • Langflow
    • Langfuse
    • Autogen
    • Relevance-AI
    • Wordware
    • Chroma
    • Pinecone
    • Weavite
    • ChatGPT
    • Gemini
    • Ollama
    • Langwatch
    • LLamaIndex
    • Amazon-Bedrock

    Agentic AI Training Course Curriculum

    Curriculum Designed by Experts

    AdobeIconDOWNLOAD CURRICULUM

    Introduction to Agentic AI

    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

    skillHands-on

    • Analyzing AI Agent Use Cases
    • Exploring Agentic AI Frameworks

    skillSkills

    • 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

    skillHands-on

    • Designing an AI agent architecture
    • Implementing different agentic AI design patterns

    skillSkills

    • Understanding Agentic AI Frameworks
    • Implementing AI Design Patterns
    • Designing Secure and Scalable AI Architectures

    Getting Started 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

    skillHands-on

    • Build a Resume Screening Application with LangChain
    • Develop a Legal Document Review Application with LangChain

    skillSkills

    • 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

    skillHands-on

    • Building a Finance Bot with LangGraph

    skillSkills

    • 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

    skillHands-on

    • Create an AI-Powered Sales Report Analyzer with LlamaIndex
    • Create a Market Research Agent with RAG & Cohere

    skillSkills

    • Implementing RAG Techniques
    • Building AI Agents with LlamaIndex and Cohere
    • Optimizing AI Retrieval Systems

    Developing AI Agents with Agno (Phidata)

    10 Topics

    Topics

    • Agents
    • Models
    • Tools
    • Knowledge
    • Chunking
    • Vector DB
    • Storage
    • Embeddings
    • Workflows
    • Developing Agents with Phidata

    skillHands-on

    • Design a Data Analysis Agent with Phidata

    skillSkills

    • 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

    skillHands-on

    • Building Multi Agent Systems with LangGraph and CrewAI

    skillSkills

    • Build a Customer Support Chatbot with LangGraph
    • Design a Stock Analysis Agent with CrewAI

    Agentic AI 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

    skillHands-on

    • Develop an AI Research Agent with Autogen

    skillSkill

    • 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

    skillHands-on

    • AI Observability with Langsmith
    • AgentOps Practical Implementation

    skillSkills

    • Monitoring AI Agent Performance
    • Managing AI Workflows
    • Implementing AI Experimentation and Observability

    Building AI Agents with Langflow and Relevance AI

    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

    skillHands-on

    • Scaling and Future Trends in No-Code AI
    • Design Your own SEO Agent with Relevance AI
    • Creating an AI Agent with Langflow

    skillSkills

    • 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

    skillHands-on

    • Build and Deploy AI Models on AWS Bedrock, Azure OpenAI, and GCP Vertex AI

    skillSkills

    • Cloud-based AI Model Deployment of Generative AI Models
    • AI Agent Development on Cloud

    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

      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

            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

               certification 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 ....
               certification projects

              Building a Finance Bot with LangGraph

              Create an AI-powered finance assistant that provides real-time financial insights and recommendations using LangGraph.
               certification projects

              Build a Resume Screening Application with LangChain

              Develop an AI-powered resume screening tool that extracts and ranks key candidate information using LangChain components.
               certification projects

              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.
               certification projects

              Design a Data Analysis Agent with Phidata

              Build an AI-powered data analysis agent using Phidata to process and visualize structured and unstructured data.
               certification projects

              Build a Customer Support Chatbot with LangGraph

              Design and deploy a multi-agent chatbot for customer support using LangGraph to handle multiple inquiries efficiently.
               certification projects

              Design a Stock Analysis Agent with CrewAI

              Develop an AI agent that analyzes stock trends, retrieves financial news, and provides investment insights using CrewAI.
               certification projects

              Develop an AI Research Agent with Autogen

              Create an AI agent that autonomously researches topics, synthesizes information, and generates structured reports using Autogen.
               certification projects

              Design Your Own SEO Agent with Relevance AI

              Create an SEO-optimized content generator using Relevance AI that analyzes keywords and suggests improvements.
               certification projects

              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.
              Edureka Certification
              John Doe
              Title
              with Grade X
              XYZ123431st Jul 2024
              The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate
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              Souvik KunduLearning to code the web, big data & cloud computing. Aspiring Developer

              I'm currently enrolled in a lot of courses offered at Edureka, so I'm attending live classes and using their study materials, course projects, have access to support staff and teachers. I can confidently say Edureka staff is very hard working and committed to help students which is reliable. Course instructors are experienced candidates from industry who know what they are teaching. Course materials are pretty comprehensive and students need to work very hard to finish course projects, pass the project interviews and gain certification. I say, it is worth it.

              December 09, 2017
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              Edureka Agentic AI Training Advantage

              WHAT I NEEDEDUREKA ADVANTAGEWHAT OTHERS OFFER
              Agentic-AI focused curriculum
              right_tickCovers LangChain, LangGraph, CrewAI, AutoGen end-to-end
              advantage_crossMany GenAI courses stop at prompt engineering
              Multi-Agent Systems training
              right_tickIncludes orchestration workflows using CrewAI + AutoGen
              advantage_crossRarely included in beginner/intermediate GenAI programs
              RAG pipeline implementation
              right_tickHands-on Agentic RAG projects included
              advantage_crossOften theoretical or limited demos only
              Tool-using AI agents
              right_tickCovers agents with external tool execution pipelines
              advantage_crossUsually chatbot-only training
              Observability (AgentOps)
              right_tickIncludes LangSmith + LangFuse monitoring workflows
              advantage_cross Most courses skip evaluation & monitoring entirely
              Real-world agent projects
              right_tickResume screener, finance assistant, research agent, chatbot
              advantage_crossUsually 1–2 chatbot demos only
              Instructor-led live classes
              right_tickWeekend cohort-based learning format
              advantage_crossMostly recorded/self-paced learning
              Portfolio-ready assignments
              right_tickMultiple guided real-world builds included
              advantage_crossLimited structured portfolio support
              Career transition readiness
              right_tickStructured roadmap toward Agent Engineer role
              advantage_crossMany courses remain research-oriented
              Edureka Advantage
              What others offer
              right_tickCovers LangChain, LangGraph, CrewAI, AutoGen end-to-end
              advantage_crossMany GenAI courses stop at prompt engineering
              right_tickIncludes orchestration workflows using CrewAI + AutoGen
              advantage_crossRarely included in beginner/intermediate GenAI programs
              right_tickHands-on Agentic RAG projects included
              advantage_crossOften theoretical or limited demos only
              right_tickCovers agents with external tool execution pipelines
              advantage_crossUsually chatbot-only training
              right_tickIncludes LangSmith + LangFuse monitoring workflows
              advantage_cross Most courses skip evaluation & monitoring entirely
              right_tickResume screener, finance assistant, research agent, chatbot
              advantage_crossUsually 1–2 chatbot demos only
              right_tickWeekend cohort-based learning format
              advantage_crossMostly recorded/self-paced learning
              right_tickMultiple guided real-world builds included
              advantage_crossLimited structured portfolio support
              right_tickStructured roadmap toward Agent Engineer role
              advantage_crossMany courses remain research-oriented

              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 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

              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.
              Have more questions?
              Course counsellors are available 24x7
              For Career Assistance :