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Master intelligent automation with the Agentic AI Training Program and boost your AI career potential.

Master the fundamentals of data analytics and learn how to use it for retrieval of business insights.

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CURRICULUM & PROJECTS

Agentic AI Training Program

    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

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    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

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    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

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    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

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    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

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    Agents

    Models

    Tools

    Knowledge

    Chunking

    Vector DB

    Storage

    Embeddings

    Workflows

    Developing Agents with Phidata

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    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

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    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

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    Langfuse Overview

    Langfuse Dashboard

    Tracing

    Evaluation

    Managing Prompts

    Experimentation

    AI Observability with Langsmith

    Setting up Langsmith

    Managing Workflows with Langsmith

    AgentOps Practical Implementation

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    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

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Not Just Studying

We’re Doing Much More!

Empowering Learning Through Real Experiences and Innovation

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