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AI Agents Training

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Build intelligent autonomous AI systems with AI Agents Training by Multisoft AI. Learn to design, develop, and deploy AI agents capable of reasoning, planning, tool usage, and task execution. Gain hands-on experience with CrewAI, LangGraph, AutoGen, MCP, and enterprise-grade AI automation frameworks.

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AI Agents Training by Multisoft AI is a comprehensive program designed to help professionals build intelligent, autonomous AI systems capable of reasoning, planning, decision-making, and task execution. As organizations increasingly adopt Generative AI solutions, AI agents have emerged as a powerful technology for automating complex workflows, improving productivity, and enabling intelligent business operations.

This training covers the complete lifecycle of AI agent development, from understanding agent architectures and Large Language Models (LLMs) to designing autonomous workflows and multi-agent systems. Participants will learn how AI agents interact with tools, APIs, databases, and external systems to perform tasks with minimal human intervention. The course includes hands-on training on leading frameworks such as CrewAI, LangGraph, AutoGen, and Model Context Protocol (MCP).

Learners will explore advanced concepts including memory management, agent communication, planning strategies, tool calling, workflow orchestration, human-in-the-loop systems, and enterprise AI automation. Through practical exercises, case studies, and real-world projects, participants will develop AI-powered assistants, business automation solutions, research agents, customer support agents, and intelligent workflow systems.

By the end of the training, learners will be able to design, deploy, and manage scalable AI agents that enhance business efficiency, automate repetitive processes, and deliver intelligent, autonomous solutions across various industries.

  • Understanding AI Agents and Agentic AI
  • Evolution of Intelligent Systems
  • AI Agents vs Traditional Automation
  • Core Components of an AI Agent
  • Agent Lifecycle and Architecture
  • Business Applications of AI Agents
  • AI Agent Ecosystem Overview

  • Introduction to Generative AI
  • Large Language Models (LLMs) Fundamentals
  • Transformer Architecture Overview
  • Prompt Engineering for AI Agents
  • Context Windows and Memory
  • Model Capabilities and Limitations
  • AI Reasoning Concepts

  • Agent Design Principles
  • Agent Roles and Responsibilities
  • Planning and Execution Models
  • Goal-Oriented Agent Design
  • Autonomous Task Execution
  • Reactive vs Proactive Agents
  • Agent Lifecycle Management

  • Role-Based Prompting
  • Task-Oriented Prompt Design
  • Chain-of-Thought Reasoning
  • ReAct Framework
  • Structured Output Generation
  • Context Management Strategies
  • Prompt Optimization Techniques

  • Importance of Memory in AI Agents
  • Short-Term Memory
  • Long-Term Memory
  • Context Retention Techniques
  • Knowledge Storage Mechanisms
  • Memory Retrieval Strategies
  • Persistent Agent Memory Architectures

  • Introduction to Tool Calling
  • Function Calling Concepts
  • API Integration for Agents
  • External Tool Connectivity
  • Database Interaction
  • File and Document Processing
  • Workflow Execution Through Tools

  • Agent Planning Strategies
  • Task Decomposition
  • Sequential Reasoning
  • Goal-Oriented Decision Making
  • Dynamic Workflow Adaptation
  • Autonomous Problem Solving
  • Intelligent Task Prioritization

  • Designing Standalone AI Agents
  • Query Processing Workflows
  • Information Retrieval
  • Task Execution Frameworks
  • User Interaction Models
  • Error Handling and Recovery
  • Agent Performance Optimization

  • Introduction to Multi-Agent Architectures
  • Agent Collaboration Models
  • Communication Protocols
  • Task Delegation Strategies
  • Cooperative Problem Solving
  • Agent Coordination Mechanisms
  • Multi-Agent Workflow Design

  • Introduction to CrewAI
  • Agents, Tasks, and Crews
  • Role-Based Agent Design
  • Crew Collaboration Workflows
  • Task Assignment and Execution
  • Multi-Agent Automation Projects
  • CrewAI Best Practices

  • Introduction to LangGraph
  • Graph-Based Workflow Design
  • Stateful Agent Systems
  • Conditional Routing
  • Multi-Step Execution Flows
  • Agent Memory Management
  • Building Agent Pipelines

  • Introduction to AutoGen
  • Conversational Agent Development
  • Multi-Agent Conversations
  • Autonomous Task Execution
  • Human-Agent Collaboration
  • AutoGen Workflow Design
  • Real-World Implementations

  • Understanding MCP Architecture
  • MCP Servers and Clients
  • Context Sharing Mechanisms
  • Tool Integration Using MCP
  • Enterprise MCP Implementations
  • Secure Context Management
  • Building MCP-Based Agent Solutions
  • Understand the fundamentals of AI Agents and Agentic AI.
  • Learn AI agent architectures and autonomous workflows.
  • Build single-agent and multi-agent systems.
  • Implement tool usage and API integration within agents.
  • Develop reasoning, planning, and decision-making capabilities.
  • Learn CrewAI, LangGraph, AutoGen, and MCP frameworks.
  • Create memory-enabled AI agents.
  • Design human-in-the-loop AI workflows.
  • Integrate AI agents with enterprise applications and databases.
  • Automate business processes using AI agents.
  • Monitor, evaluate, and optimize agent performance.
  • Deploy scalable AI agent solutions for real-world applications.

AI Agents are intelligent software systems that can autonomously perform tasks, make decisions, interact with tools, and execute workflows using Large Language Models (LLMs) and external data sources.

This training is ideal for AI developers, software engineers, automation professionals, solution architects, data scientists, and anyone interested in building autonomous AI-powered applications.

The training covers AI agent architecture, agent frameworks, tool integration, memory management, planning and reasoning, multi-step task execution, autonomous workflows, and real-world AI agent applications.

Basic programming knowledge is recommended, as the course involves working with AI frameworks, APIs, automation tools, and agent development concepts.

Participants will learn how to design, develop, deploy, and manage AI agents capable of performing complex tasks, integrating with external systems, automating business processes, and supporting enterprise AI initiatives.

course 1

$ 350 $ 350

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Lowest Price & High Quality

This Course Includes:
  • Globally Recognized Certification
  • 20+ Hrs. of Expert-Led Training
  • Interactive Live Masterclasses
  • Practical, Hands-On Learning
  • Build Your Own AI-Powered App
  • multisoft ai tools Explore a Multiple AI Tools
  • multisoft ai tools Unlimited Practice Assessments
  • multisoft ai tools Lifetime LMS Access
  • multisoft ai tools Recorded Live Sessions
Training Module

Choose your own comfortable learning experience.

One to One Training

20 hrs to Kickstart Your Training
  • 30 hours of personalized Salesforce training
  • Direct one-to-one sessions with expert trainers
  • 100% practical-oriented classes tailored to your pace
  • Includes resources and study materials
  • Latest version curriculum covered in detail
  • Flexible timing to suit your schedule
  • 24×7 learner assistance
  • Certification guidance provided
  • Post-training community and expert support
  • Lifetime access to training materials
  • Personalized career interview tips

Live Online (Instructor-Led)

20 hrs of Remote Classes
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  • Includes Self-Paced learning access
  • Live demonstrations of industry-ready skills
  • Virtual instructor-led training (VILT) classes
  • Real-time projects & certification guidance

Corporate Training

Customized Group Learning for Teams
  • Tailored curriculum to meet your business needs
  • Flexible scheduling (on-site or virtual)
  • Industry expert trainers with domain experience
  • Real-world case studies & hands-on practice
  • Focus on improving team productivity & skill application
  • Custom reporting & performance tracking
  • Access to post-training resources
  • Long-term upskilling partnership options

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