This repo is for the Linkedin Learning course: Build with AI: Creating Agents with CrewAI

Self-learning prompt injection detection engine — 25 input detectors (10 languages), 5 output scanners, PII redaction, red team self-testing, F1: 96.0% with 0% false positives. Docker, GitHub Action, pre-commit, FastAPI/Flask/Django/LangChain/CrewAI/Dify/n8n.

An instructional repo for learning dspy+crewai integration

The CrewAI Machine Learning Assistant is a Streamlit-based application designed to guide users through the process of defining, assessing, and solving machine learning problems. It leverages AI agents from CrewAI to assist in problem clarification, data assessment, and model recommendation.

Learning CrewAI is a Python project that demonstrates the CrewAI framework for building AI-powered agent crews

Collaborative learning on AI Agent including LangGraph, CrewAI, AutoGen, Open AI Swarm, llamaindex Agent

🛠️ Explore hands-on notebooks to master LLMs, RAG, LangChain, CrewAI, and multi-agent systems for effective AI learning and experimentation.

An AI-powered EdTech platform leveraging RAG, LLMs, CrewAI, and Streamlit to enhance personalized learning, automate assessments, and provide intelligent tutoring. It can generate quizzes from PDFs and assist with doubt-solving through AI-driven interactions🚀

Complete RAG learning path: Basic to Advanced RAG, Multi-Agent Systems (LangChain, AutoGen, CrewAI, LangGraph, Bedrock), Knowledge Graphs, Production Pipelines, Cloud Deployments

This project uses CrewAI to build AI agents that create a personalized learning path based on a user’s goals, knowledge, and learning style. It analyzes input, identifies gaps, finds resources, and presents a structured, goal-oriented plan.

Learn how to use crewAI, an open-source library, to automate tasks and further create Multi AI Agents.

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This is the Deep Learning Multi Agents CrewAI repo

CrewAI Multi-Agent Workshop - Learning project for building multi-agent systems with CrewAI

This repository holds all the exercises explained in the Multi AI Agent Systems with crewAI from DeepLearning.ai using a most recent version of CrewAI.

This is the Deep Learning Practical Multi AI Agents and Advanced Use Cases with crewAI Repository

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A self-evolving AI system built with CrewAI that demonstrates hierarchical agent collaboration and autonomous learning capabilities.

Sample project demonstrating data mapping capabilities of GPT orchestrated through CrewAI, developed as part of Fontys Open Learning program.

A CrewAI multi-agent YouTube learning assistant that identifies top channels, curates high-quality content on topics of interest, and generates quizzes for interactive learning.

Following my AI Agent Journey, I am learning CrewAI and working on a project to search, write and publish blogs.

A multi-agent AI system built with CrewAI that automates content summarization, quiz generation, and performance evaluation to enhance the learning experience.

CrewAI-MultiAgent is my learning journey through the CrewAI Multi-Agent course. I'll be updating this repo with insights, code, and projects as I explore LLM-based agents, task planning, collaboration, and real-world applications. Follow along for hands-on experiments and implementations! 🚀

An End-to-End Multi-Agent AI System built with CrewAI that conducts comprehensive technical interviews across Data Science, Machine Learning, Agentic AI, and RAG domains.

The CrewAI Machine Learning Assistant is a command line application designed to kickstart your machine learning projects. It leverages a team of AI agents to guide you through the initial steps of defining, assessing, and solving machine learning problems.

Course Planning Assistant AI is an AI-powered multi-agent system that generates personalized course and learning plans based on user goals, skills, and preferences, using CrewAI for intelligent task orchestration.

This repository is a personal learning hub for exploring AI agents, Retrieval-Augmented Generation (RAG) techniques, and modern AI frameworks like LangChain, CrewAI, and more. It documents key learnings and hosts small experiments designed to deepen understanding of agentic AI systems.

"A complete learning documentary of AI Agents — from scratch to real-world implementations. Dive deep into prompting techniques, intelligent workflows, autonomous agents, LangChain, CrewAI, and more, all documented step-by-step with practical insights and project implementations.".

🚀 An AI-powered blog automation system using CrewAI. It employs specialized agents for YouTube research and blog writing, leveraging channel search tools to fetch video insights and generate engaging, simplified blog content on Latest trends in AI and Machine Learning.

This project involves the development of a sophisticated multi-agent system designed to automate swing trading on the Toronto Stock Exchange (TSX). Leveraging the CrewAI framework and Python, the system integrates machine learning models to analyze market data, evaluate trading strategies.