Crewai Complete Course: Agent Crews, Rag,Flows,Studio [2025]

From Beginner to Expert: Create AI Agent Teams for Finance, Health, Travel & HR system

What you'll learn

Build specialized AI agents for finance research, health analysis, trip planning, and HR automation that work collaboratively to solve complex business problems

Master CrewAI RAG systems using local models including Deepseek and Llama to create intelligent agents that access and process custom knowledge bases.

Design advanced multi-agent workflows using CrewAI Flows with sequential processing, parallel execution, and intelligent routing capabilities.

Create production-ready agent systems using CrewAI Studio's no-code interface and deploy them from local development to enterprise environments.

Implement real-world agent crews that automate entire business processes including research analysis, data processing, and decision-making workflows

Requirements

Basic python

Description

Master the future of AI automation with CrewAI - the revolutionary framework that transforms how businesses build intelligent agent systems. This comprehensive course takes you from complete beginner to expert, teaching you to create production-ready multi-agent crews for real-world applications.Build Powerful AI Agent Teams That Work Together SeamlesslyCreate specialized agents for Finance Research, Health Analytics, Trip Planning & HR AutomationMaster RAG systems with local models including Deepseek and Llama integrationDesign advanced workflows using CrewAI Flows for sequential and parallel agent coordinationImplement no-code solutions with CrewAI Studio for rapid agent developmentDeploy production systems from local development to enterprise-ready applicationsWhy CrewAI is revolutionizing AI development: Unlike single AI models, CrewAI enables you to orchestrate teams of specialized agents that collaborate, share memory, and execute complex multi-step tasks with unprecedented efficiency. Companies are already using these systems to automate entire business processes that previously required human teams.What makes this course unique: You'll build 10+ real-world projects including financial analysts that research stocks, health researchers that analyze medical data, trip planners that create complete itineraries, and HR systems with intelligent routing. Each project uses cutting-edge techniques including local model integration and advanced flow orchestration.Perfect for: Developers wanting to build AI automation systems, business professionals seeking to implement agent-based solutions, and entrepreneurs creating AI-powered products. No prior AI experience required - we start from the fundamentals and build to advanced enterprise patterns.By course completion, you'll have a portfolio of working agent systems and the skills to architect sophisticated AI automation solutions for any industry.Word count: 296 wordsKey highlights formatted for maximum impact:Bolded action-oriented benefits that clearly state what students will achieveSpecific project mentions showing practical applicationsTechnical depth indicators like "RAG systems," "local models," and "production-ready"Target audience clarity explaining who benefits most from the courseUnique value proposition explaining why CrewAI matters in the current AI landscapeResults-focused ending emphasizing the portfolio and skills students will gain

Overview

Section 1: Crewal AI Intro

Lecture 1 CrewAi overview

Lecture 2 UV setup install

Lecture 3 Install Visual studio

Lecture 4 All code resources

Section 2: Finance Research Analyst Agent

Lecture 5 Project setup Research analyst

Lecture 6 Research Analayst Agent Overview

Lecture 7 Serper API and OpenAi Api Key

Lecture 8 Research Analyst and SerperDev tool

Lecture 9 Senior Content writer Agent

Lecture 10 Researcher and Content writer Task

Lecture 11 Demo Researcher Analyst Agent

Lecture 12 Frontend Streamlit chatbo

Lecture 13 Frontend run and code

Lecture 14 Frontend and Backend Agent Inegration

Lecture 15 Demo Senior Research Analyst with Frontend Streamlit

Section 3: Health Researcher Agent

Lecture 16 CrewAI Researcher Setup

Lecture 17 CrewAi Researcher high level design

Lecture 18 Agent and Task Config Yaml

Lecture 19 CrewAi Multiagent

Lecture 20 Demo CrewAI health Multiagent

Lecture 21 Save Agent result in Blog file

Section 4: Trip Planner Agent

Lecture 22 Paris CrewAI Trip Planner Architecture

Lecture 23 Trip Planner CrewAi Setup

Lecture 24 API KEY OF SERPER API BROWSERLESS AND OPENAI API

Lecture 25 Search tool serper

Lecture 26 Browser tool

Lecture 27 Calculator tool

Lecture 28 Agent Task Identify Gather Plan

Lecture 29 Create Main Agents

Lecture 30 Client CLI APP

Lecture 31 CrewAI Main Run method

Lecture 32 Demo Trip Planner Agent

Lecture 33 Streamlit Backend Integration with Agent

Lecture 34 Streamlit Front end Trip Planner

Lecture 35 Demo Trip Planner Agent with Frontend Streamlit

Lecture 36 Fasp trip Planner Overview

Lecture 37 Fast API Agent Code

Lecture 38 Demo Fast APi Agent

Section 5: CrewAI Rag System

Lecture 39 CrewAi RAG agent intro

Lecture 40 Setup project crewAI Rag

Lecture 41 RAG custom tool

Lecture 42 Config agent and task yaml

Lecture 43 Crew Agents Retriever Synthesizer

Lecture 44 Main Method

Lecture 45 Serper API key

Lecture 46 OpenAI api key and billing

Lecture 47 Env API key setup openai serper

Lecture 48 Demo CrewAI RAG agent openai

Section 6: Deepseek local CrewAI RAG agent

Lecture 49 Ollama setup deepseek

Lecture 50 Deepseek R1 Crew Agents

Lecture 51 Frontend deepseek RAG Agent chat

Lecture 52 Demo Deepseek CrewAI Rag Agent Chatbot

Section 7: Llama local CrewAI RAG agent

Lecture 53 LLama run with ollama locally

Lecture 54 Llama crew Multi Agents

Lecture 55 Llama Streamlit frontend rag agent

Lecture 56 Demo LLama CrewAI Rag agents

Section 8: CrewAI Flows Content writer

Lecture 57 CrewAI Flows Overview

Lecture 58 Install crewAI

Lecture 59 CrewAI Poem Flow Project setup

Lecture 60 Install dependencies flow

Lecture 61 Flow Architecture

Lecture 62 CrewAI Agent Flow Code

Lecture 63 Demo CrewAI Poem Flow Agents

Section 9: CrewAI Flow Researcher Sequential agent

Lecture 64 CrewAI Flow Scientist Agent Overview

Lecture 65 CrewAI Flow Agent setup and Config

Lecture 66 Content Crew Flow Agent

Lecture 67 Main Flow Creation for Guideline

Lecture 68 Main Researcher Sequenital agent Flow

Lecture 69 Demo Researcher Sequenital agent Flow

Section 10: Advance CrewAI HR Multi Agent Flow with Router

Lecture 70 CrewAI HR advanced agent Architecture

Lecture 71 CrewAI HR agent flow setup

Lecture 72 HR agent flow project structure

Lecture 73 Candidate selection agent

Lecture 74 Job description

Lecture 75 HR feedback agent

Lecture 76 Candidate score save

Lecture 77 Profile score agent flow

Lecture 78 Router Agent Human in the loop feedback

Lecture 79 Email Response Agent Flow

Lecture 80 Demo CrewAI HR Multi Agent Flow

Section 11: CrewAI Studio Create Agent with No code

Lecture 81 CrewAI Studio overview

Lecture 82 OpenAI api key and billing

Lecture 83 Serper API key

Lecture 84 CrewAI Studio create product specialist agent

Lecture 85 CrewAI Studio Features vs prices agents

Lecture 86 Deployment Of Agent with CrewAI studio

Section 12: Appendix 1-Pydantic for LLM

Lecture 87 Pydantic use case for LLM

Lecture 88 Project setup pydantic

Lecture 89 Pydantic LLM Basic

Lecture 90 Pydantic optional and JSON Input

Lecture 91 Create structured output for LLM

Lecture 92 Generate Structured output via prompt

Lecture 93 Handle Error

Lecture 94 Fix error with feedback loop and LLM

Lecture 95 Prompt Using JSON schema

Lecture 96 Pydantic Model directly to API call OPENAI

Lecture 97 Anthropic API KEY

Lecture 98 Pydantic Model directly to API call Anthropic

Lecture 99 Investigate class inheritance

Lecture 100 Additing tool to Pydantic model Overview

Lecture 101 Add FAQ tool to Pydantic Model

Lecture 102 Create Support Ticket Pydantic Model

Lecture 103 Order status and FAQ tool

Lecture 104 Get Tools Output

Lecture 105 Final Output Flow Overview

Lecture 106 Next Step Pydantic Learning

Lecture 107 Pydantic validate json file

Section 13: Appendix 2- Intro to generative AI

Lecture 108 Generative AI Intro

Lecture 109 Attention Intro

Lecture 110 Attention word Embedding

Lecture 111 Attention Positional Encoding

Lecture 112 Q_K_V_ Attention

Lecture 113 Q_K_V_ Transformer

Lecture 114 Add And Norm In Transfer Block

Lecture 115 Feed Forward Network

Lecture 116 Self Attention Code Intro

Lecture 117 Multi-head Attention Code Overview

Lecture 118 PyTorch Transformer Create word Embedding

Lecture 119 PyTorch Transformer positional Encoding

Lecture 120 PyTorch Calculate Multi-head Attention

Lecture 121 PyTorch Transformer Block Full

Lecture 122 Decoder Transformer Intro

Lecture 123 Decoder output Embedding Feedforward network

Lecture 124 PyTorch Decoder Block

Lecture 125 PyTorch Transformer Decoder

Lecture 126 PyTorch Entire Transformer

Lecture 127 PyTorch Entire Transformer Fwd And Interface

Lecture 128 PyTorch Testing Transformer Code

Lecture 129 PyTorch Running Transformer Code

Agentic AI,CrewAI